The Office of Management and Enterprise Services in the State of Oklahoma has made its purchase credit card transactions available. This dataset contains information on purchases made through the purchase card programs administered by the state and higher education institutions.
library(dplyr)
library(DataExplorer)
library(ggplot2)
library(plotly)
library(kableExtra)
library(reshape2)
#load data
ccard <- read.csv("res_purchase_card.csv")
#explore data
dim(ccard)
## [1] 442458 11
summary(ccard)
## Year.Month Agency.Number
## Min. :201307 Min. : 1000
## 1st Qu.:201309 1st Qu.: 1000
## Median :201401 Median :47700
## Mean :201357 Mean :42786
## 3rd Qu.:201404 3rd Qu.:76000
## Max. :201406 Max. :98000
##
## Agency.Name
## OKLAHOMA STATE UNIVERSITY :115995
## UNIVERSITY OF OKLAHOMA : 76143
## UNIV. OF OKLA. HEALTH SCIENCES CENTER: 58247
## DEPARTMENT OF CORRECTIONS : 22322
## DEPARTMENT OF TOURISM AND RECREATION : 17232
## DEPARTMENT OF TRANSPORTATION : 15689
## (Other) :136830
## Cardholder.Last.Name Cardholder.First.Initial
## JOURNEY HOUSE TRAVEL INC: 10137 J : 55031
## UNIVERSITY AMERICAN : 7219 G : 42251
## JOURNEY HOUSE TRAVEL : 4693 D : 38120
## Heusel : 4212 M : 35352
## Hines : 3423 S : 34698
## Bowers : 2448 C : 33213
## (Other) :410326 (Other):203793
## Description Amount
## GENERAL PURCHASE :247187 Min. : -42863.0
## AIR TRAVEL : 29584 1st Qu.: 30.9
## ROOM CHARGES : 18120 Median : 104.9
## AT&T SERVICE PAYMENT ITM : 2657 Mean : 425.0
## 001 Priority 1LB PCE: 2005 3rd Qu.: 345.0
## 000000000000000000000000 : 1828 Max. :1903858.4
## (Other) :141077
## Vendor Transaction.Date
## STAPLES : 14842 09/11/2013 12:00:00 AM: 2122
## AMAZON MKTPLACE PMTS : 12197 08/07/2013 12:00:00 AM: 2108
## WW GRAINGER : 12076 01/14/2014 12:00:00 AM: 2059
## Amazon.com : 10766 01/16/2014 12:00:00 AM: 2009
## BILL WARREN OFFICE PRODUC: 4479 09/05/2013 12:00:00 AM: 1999
## LOWES #00241 : 4231 10/01/2013 12:00:00 AM: 1996
## (Other) :383867 (Other) :430165
## Posted.Date
## 01/13/2014 12:00:00 AM: 3256
## 04/14/2014 12:00:00 AM: 3163
## 03/10/2014 12:00:00 AM: 3139
## 03/03/2014 12:00:00 AM: 3101
## 09/16/2013 12:00:00 AM: 3062
## 01/20/2014 12:00:00 AM: 3032
## (Other) :423705
## Merchant.Category.Code..MCC.
## STATIONERY, OFFICE SUPPLIES, PRINTING AND WRITING PAPER: 24860
## BOOK STORES : 21981
## INDUSTRIAL SUPPLIES NOT ELSEWHERE CLASSIFIED : 21669
## DENTAL/LABORATORY/MEDICAL/OPHTHALMIC HOSP EQIP AND SUP.: 20183
## GROCERY STORES,AND SUPERMARKETS : 17152
## MISCELLANEOUS AND SPECIALTY RETAIL STORES : 13335
## (Other) :323278
colnames(ccard)
## [1] "Year.Month" "Agency.Number"
## [3] "Agency.Name" "Cardholder.Last.Name"
## [5] "Cardholder.First.Initial" "Description"
## [7] "Amount" "Vendor"
## [9] "Transaction.Date" "Posted.Date"
## [11] "Merchant.Category.Code..MCC."
nrow(ccard)
## [1] 442458
#change column names
colnames(ccard) <-
c(
'Year_Month',
'Agency_Number',
'Agency_Name',
'Cardholder_Last_Name',
'Cardholder_First_Initial',
'Description',
'Amount',
'Vendor',
'Transaction_Date',
'Posted_Date',
'Merchant_Category'
)
#view head of ccard
kable(head(ccard)) %>% kable_styling(latex_options = "scale_down")
| Year_Month | Agency_Number | Agency_Name | Cardholder_Last_Name | Cardholder_First_Initial | Description | Amount | Vendor | Transaction_Date | Posted_Date | Merchant_Category |
|---|---|---|---|---|---|---|---|---|---|---|
| 201307 | 1000 | OKLAHOMA STATE UNIVERSITY | Mason | C | GENERAL PURCHASE | 890.00 | NACAS | 07/30/2013 12:00:00 AM | 07/31/2013 12:00:00 AM | CHARITABLE AND SOCIAL SERVICE ORGANIZATIONS |
| 201307 | 1000 | OKLAHOMA STATE UNIVERSITY | Mason | C | ROOM CHARGES | 368.96 | SHERATON HOTEL | 07/30/2013 12:00:00 AM | 07/31/2013 12:00:00 AM | SHERATON |
| 201307 | 1000 | OKLAHOMA STATE UNIVERSITY | Massey | J | GENERAL PURCHASE | 165.82 | SEARS.COM 9300 | 07/29/2013 12:00:00 AM | 07/31/2013 12:00:00 AM | DIRCT MARKETING/DIRCT MARKETERS–NOT ELSEWHERE CLASSIFIED |
| 201307 | 1000 | OKLAHOMA STATE UNIVERSITY | Massey | T | GENERAL PURCHASE | 96.39 | WAL-MART #0137 | 07/30/2013 12:00:00 AM | 07/31/2013 12:00:00 AM | GROCERY STORES,AND SUPERMARKETS |
| 201307 | 1000 | OKLAHOMA STATE UNIVERSITY | Mauro-Herrera | M | HAMMERMILL COPY PLUS COPY EA | 125.96 | STAPLES DIRECT | 07/30/2013 12:00:00 AM | 07/31/2013 12:00:00 AM | STATIONERY, OFFICE SUPPLIES, PRINTING AND WRITING PAPER |
| 201307 | 1000 | OKLAHOMA STATE UNIVERSITY | Mauro-Herrera | M | GENERAL PURCHASE | 394.28 | KYOCERA DOCUMENT SOLUTION | 07/29/2013 12:00:00 AM | 07/31/2013 12:00:00 AM | OFFICE, PHOTOGRAPHIC, PHOTOCOPY, AND MICROFILM EQUIPMENT |
#view count for each month
kable(table(ccard$Year_Month))
| Var1 | Freq |
|---|---|
| 201307 | 37635 |
| 201308 | 39314 |
| 201309 | 38762 |
| 201310 | 40266 |
| 201311 | 34275 |
| 201312 | 26969 |
| 201401 | 37230 |
| 201402 | 35831 |
| 201403 | 38188 |
| 201404 | 39249 |
| 201405 | 36784 |
| 201406 | 37955 |
#Add Monetary feature
#Add Max, Average and Median Amount Ratio Features by agency_name and merchant category
avg_agency <- ccard %>% group_by(Agency_Name, Merchant_Category) %>%
summarise(
mean_category_amount = mean(Amount),
median_category_amount = median(Amount),
mean_count_trans = n()
)
#view head of avg_agency
kable(head(avg_agency)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | mean_category_amount | median_category_amount | mean_count_trans |
|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:right;"> 508.48600 </td> <td style="text-align:right;"> 415.85 </td> <td style="text-align:right;"> 5 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 492.98809 | 620.60 | 89 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BEST WESTERN </td> <td style="text-align:right;"> 94.81143 </td> <td style="text-align:right;"> 83.00 </td> <td style="text-align:right;"> 7 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BOOK STORES | 131.82414 | 80.66 | 29 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOKS, PERIODICALS AND NEWSPAPERS </td> <td style="text-align:right;"> 275.00000 </td> <td style="text-align:right;"> 275.00 </td> <td style="text-align:right;"> 1 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 235.88067 | 300.00 | 15 |
# Append the max, average and median statistics back to the data to derive the ratios.
# Select the most recent 4 transactions
per_agency_category <-
ccard %>% group_by(Agency_Name, Merchant_Category, Year_Month) %>%
summarise(
max_amount = max(Amount),
mean_amount = mean(Amount),
median_amount = median(Amount),
count_trans = n()
) %>%
left_join(avg_agency, by = c('Agency_Name', 'Merchant_Category')) %>%
mutate(
max_amount_ratio = max_amount / mean_category_amount,
mean_amount_ratio = mean_amount / mean_category_amount,
median_amount_ratio = median_amount / median_category_amount,
mean_count_ratio = count_trans / mean_count_trans
) %>%
select(
-mean_category_amount,
-median_category_amount,
-mean_count_trans,-max_amount,
-mean_amount,
-median_amount,
-count_trans
) %>%
top_n(-4) # Use top_n(xx) to select the top xx rows, and top_n(-xx) for the bottom xx rows
#summary
summary(per_agency_category)
## Agency_Name
## OKLAHOMA STATE UNIVERSITY : 1359
## UNIVERSITY OF OKLAHOMA : 1080
## UNIV. OF OKLA. HEALTH SCIENCES CENTER: 749
## DEPARTMENT OF TOURISM AND RECREATION : 739
## DEPARTMENT OF CORRECTIONS : 713
## GRAND RIVER DAM AUTH. : 682
## (Other) :20764
## Merchant_Category
## STATIONERY, OFFICE SUPPLIES, PRINTING AND WRITING PAPER: 438
## MISCELLANEOUS AND SPECIALTY RETAIL STORES : 435
## BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED : 401
## GOVERNMENT SERVICES--NOT ELSEWHERE CLASSIFIED : 381
## CHARITABLE AND SOCIAL SERVICE ORGANIZATIONS : 363
## AMERICAN AIRLINES : 350
## (Other) :23718
## Year_Month max_amount_ratio mean_amount_ratio median_amount_ratio
## Min. :201307 Min. : -Inf Min. : -Inf Min. : -Inf
## 1st Qu.:201310 1st Qu.:0.590 1st Qu.:0.4802 1st Qu.:0.7564
## Median :201401 Median :1.001 Median :0.9675 Median :1.0000
## Mean :201357 Mean : NaN Mean : NaN Mean : NaN
## 3rd Qu.:201404 3rd Qu.:1.899 3rd Qu.:1.2534 3rd Qu.:1.4870
## Max. :201406 Max. : Inf Max. : Inf Max. : Inf
## NA's :22 NA's :22
## mean_count_ratio
## Min. :0.002833
## 1st Qu.:0.062500
## Median :0.111111
## Mean :0.248170
## 3rd Qu.:0.333333
## Max. :1.000000
##
#some category summations equaled zero, resulted in INF ratio outputs, remove
per_agency_category <-
per_agency_category[is.finite(per_agency_category$max_amount_ratio),]
#view head of per_agency_category
kable(head(per_agency_category)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | max_amount_ratio | mean_amount_ratio | median_amount_ratio | mean_count_ratio |
|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:right;"> 201307 </td> <td style="text-align:right;"> 1.4822040 </td> <td style="text-align:right;"> 0.8296984 </td> <td style="text-align:right;"> 1.0000000 </td> <td style="text-align:right;"> 0.6000000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | 201308 | 0.0749676 | 0.0749676 | 0.0916677 | 0.2000000 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:right;"> 201401 </td> <td style="text-align:right;"> 2.4359373 </td> <td style="text-align:right;"> 2.4359373 </td> <td style="text-align:right;"> 2.9785740 </td> <td style="text-align:right;"> 0.2000000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 201307 | 1.7274251 | 1.4453020 | 1.1627457 | 0.1348315 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:right;"> 201308 </td> <td style="text-align:right;"> 1.4637270 </td> <td style="text-align:right;"> 1.0760503 </td> <td style="text-align:right;"> 1.1627457 </td> <td style="text-align:right;"> 0.0561798 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 201312 | 1.0986067 | -0.1045326 | 0.1456655 | 0.0674157 |
#create new DF, add Max to year_month column
max_per_agency_category <- per_agency_category %>%
mutate(Year_Month = paste("Max", Year_Month, sep = "_")) %>%
select(-mean_amount_ratio,-mean_count_ratio,-median_amount_ratio)
#view head of max_per_agency_category
kable(head(max_per_agency_category)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | max_amount_ratio |
|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> Max_201307 </td> <td style="text-align:right;"> 1.4822040 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | Max_201308 | 0.0749676 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> Max_201401 </td> <td style="text-align:right;"> 2.4359373 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | Max_201307 | 1.7274251 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:left;"> Max_201308 </td> <td style="text-align:right;"> 1.4637270 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | Max_201312 | 1.0986067 |
#create new DF, add Med to year_month column
med_per_agency_category <- per_agency_category %>%
mutate(Year_Month = paste("Med", Year_Month, sep = "_")) %>%
select(-mean_amount_ratio,-mean_count_ratio,-max_amount_ratio)
#view head of med_per_agency_category
kable(head(med_per_agency_category)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | median_amount_ratio |
|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> Med_201307 </td> <td style="text-align:right;"> 1.0000000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | Med_201308 | 0.0916677 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> Med_201401 </td> <td style="text-align:right;"> 2.9785740 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | Med_201307 | 1.1627457 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:left;"> Med_201308 </td> <td style="text-align:right;"> 1.1627457 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | Med_201312 | 0.1456655 |
#create new DF, add Mean to year_month column
mean_per_agency_category <- per_agency_category %>%
mutate(Year_Month = paste("Mean", Year_Month, sep = "_")) %>%
select(-max_amount_ratio,-mean_count_ratio,-median_amount_ratio)
#view head of mean_per_agency_category
kable(head(mean_per_agency_category)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | mean_amount_ratio |
|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> Mean_201307 </td> <td style="text-align:right;"> 0.8296984 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | Mean_201308 | 0.0749676 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> Mean_201401 </td> <td style="text-align:right;"> 2.4359373 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | Mean_201307 | 1.4453020 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:left;"> Mean_201308 </td> <td style="text-align:right;"> 1.0760503 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | Mean_201312 | -0.1045326 |
# Max variable: Use "dcast" in Library "reshape2" to organize the data so each row
#is a merchant category of an agent.
max_wide <-
dcast(max_per_agency_category,
Agency_Name + Merchant_Category ~ Year_Month)
max_wide = as.matrix(max_wide)
max_wide[is.na(max_wide)] <- 0
max_wide = as.data.frame(max_wide)
#view head
kable(head(max_wide)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Max_201307 | Max_201308 | Max_201309 | Max_201310 | Max_201311 | Max_201312 | Max_201401 | Max_201402 | Max_201403 | Max_201404 | Max_201405 | Max_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 1.482204e+00 </td> <td style="text-align:left;"> 7.496765e-02 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2.435937e+00 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 1.727425e+00 | 1.463727e+00 | 0 | 0 | 0 | 1.098607e+00 | 1.127816e+00 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BEST WESTERN </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.884583e+00 </td> <td style="text-align:left;"> 7.383076e-01 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 8.754219e-01 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BOOK STORES | 2.911303e+00 | 5.317691e-01 | 3.179236e-01 | 4.301184964 | 0 | 6.221167e-01 | 0 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOKS, PERIODICALS AND NEWSPAPERS </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.000000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 4.027460e-02 | 1.271830e+00 | 0 | 0 | 1.801759e+00 | 1.839701e+00 | 2.204505e+00 | 0 | 0 | 0 | 0 | 0 |
# Median variable: Use "dcast" in Library "reshape2" to organize the data so each
#row is a merchant category of an agent.
med_wide <-
dcast(med_per_agency_category,
Agency_Name + Merchant_Category ~ Year_Month)
med_wide = as.matrix(med_wide)
med_wide[is.na(med_wide)] <- 0
med_wide = as.data.frame(med_wide)
#view head
kable(head(med_wide)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Med_201307 | Med_201308 | Med_201309 | Med_201310 | Med_201311 | Med_201312 | Med_201401 | Med_201402 | Med_201403 | Med_201404 | Med_201405 | Med_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 1.000000e+00 </td> <td style="text-align:left;"> 9.166767e-02 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2.978574e+00 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 1.162746e+00 | 1.162746e+00 | 0 | 0 | 0 | 0.14566549 | 8.959072e-01 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BEST WESTERN </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2.152771e+00 </td> <td style="text-align:left;"> 8.433735e-01 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.000000e+00 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BOOK STORES | 8.430449e-01 | 8.690801e-01 | 5.195884e-01 | 1.640218200 | 0 | 0.72198116 | 0 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOKS, PERIODICALS AND NEWSPAPERS </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.000000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 3.166667e-02 | 1.881667e-01 | 0 | 0 | 1.416666667 | 1.38158333 | 5.000000e-01 | 0 | 0 | 0 | 0 | 0 |
# Mean variable: Use "dcast" in Library "reshape2" to organize the data so each
#row is a merchant category of an agent.
mean_wide <-
dcast(mean_per_agency_category,
Agency_Name + Merchant_Category ~ Year_Month)
mean_wide = as.matrix(mean_wide)
mean_wide[is.na(mean_wide)] <- 0
mean_wide = as.data.frame(mean_wide)
#view head
kable(head(mean_wide)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Mean_201307 | Mean_201308 | Mean_201309 | Mean_201310 | Mean_201311 | Mean_201312 | Mean_201401 | Mean_201402 | Mean_201403 | Mean_201404 | Mean_201405 | Mean_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 8.296984e-01 </td> <td style="text-align:left;"> 7.496765e-02 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2.435937e+00 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 1.445302e+00 | 1.076050e+00 | 0 | 0 | 0 | -0.1045326132 | 8.628471e-01 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BEST WESTERN </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.884583e+00 </td> <td style="text-align:left;"> 7.383076e-01 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 8.754219e-01 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BOOK STORES | 9.944309e-01 | 5.317691e-01 | 3.179236e-01 | 1.403551754 | 0 | 0.4417627979 | 0 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOKS, PERIODICALS AND NEWSPAPERS </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.000000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 4.027460e-02 | 5.065414e-01 | 0 | 0 | 1.8017585163 | 1.7571384966 | 9.489262e-01 | 0 | 0 | 0 | 0 | 0 |
#merge dataframes
model_df_amt <-
left_join(max_wide, mean_wide, by = c('Agency_Name', 'Merchant_Category'))
model_df_amt <-
merge(model_df_amt,
med_wide,
by = c("Agency_Name", "Merchant_Category"))
#Add Recency feature (time since last transaction) by agency_name and merchant category
#Add Max, Average and Median Recency Ratio Features by agency_name and merchant category
#create new DF grouped by agencies and by Merchant_Category,
#with Recency column
time_by_Merchant_Category <-
ccard %>% group_by(Agency_Name, Merchant_Category) %>%
mutate(Transaction_Date = as.Date(Transaction_Date, format = "%m/%d/%Y %H:%M")) %>%
arrange(Agency_Name, Merchant_Category, Transaction_Date) %>%
mutate(Recency = Transaction_Date - lag(Transaction_Date))
#view head of time_by_Merchant_Category
kable(head(time_by_Merchant_Category[, c("Agency_Number",
"Agency_Name",
"Merchant_Category",
"Transaction_Date",
"Recency")])) %>% kable_styling(latex_options = "scale_down")
| Agency_Number | Agency_Name | Merchant_Category | Transaction_Date | Recency |
|---|---|---|---|---|
| 26500 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 2013-06-29 </td> <td style="text-align:left;"> NA </td> </tr> <tr> <td style="text-align:right;"> 26500 </td> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | 2013-07-01 | 2 days |
| 26500 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 2013-07-12 </td> <td style="text-align:left;"> 11 days </td> </tr> <tr> <td style="text-align:right;"> 26500 </td> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | 2013-08-01 | 20 days |
| 26500 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 2014-01-21 </td> <td style="text-align:left;"> 173 days </td> </tr> <tr> <td style="text-align:right;"> 26500 </td> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 2013-07-03 | NA |
#sort by recency
Recency_cat_sorted <-
time_by_Merchant_Category %>% arrange(Merchant_Category, Recency) %>% na.omit
#Calculate the average and median recency by agency_name and merchant category
avg_recency <-
Recency_cat_sorted %>% group_by(Agency_Name, Merchant_Category) %>%
summarise(
mean_recency_amount = mean(Recency),
median_recency_amount = median(Recency),
mean_count_recency = n()
)
#view head of avg_recency
kable(head(avg_recency)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | mean_recency_amount | median_recency_amount | mean_count_recency |
|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 51.50000 days </td> <td style="text-align:left;"> 15.5 days </td> <td style="text-align:right;"> 4 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 2.37500 days | 0.5 days | 88 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BEST WESTERN </td> <td style="text-align:left;"> 28.33333 days </td> <td style="text-align:left;"> 0.0 days </td> <td style="text-align:right;"> 6 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BOOK STORES | 6.50000 days | 1.0 days | 28 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED </td> <td style="text-align:left;"> 14.64286 days </td> <td style="text-align:left;"> 9.0 days </td> <td style="text-align:right;"> 14 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
CATALOG MERCHANTS | 44.50000 days | 44.5 days | 2 |
# Append the average and median recency statistics back to the data to derive the ratios.
# Select the most recent 4 transactions
per_agency_category_rec <-
Recency_cat_sorted %>% group_by(Agency_Name, Merchant_Category, Year_Month) %>%
summarise(
max_rec = max(Recency),
mean_rec = mean(Recency),
median_rec = median(Recency),
count_rec = n()
)
per_agency_category_rec <-
left_join(per_agency_category_rec,
avg_recency,
by = c('Agency_Name', 'Merchant_Category'))
#view class
lapply(per_agency_category_rec, class)
## $Agency_Name
## [1] "factor"
##
## $Merchant_Category
## [1] "factor"
##
## $Year_Month
## [1] "integer"
##
## $max_rec
## [1] "difftime"
##
## $mean_rec
## [1] "difftime"
##
## $median_rec
## [1] "difftime"
##
## $count_rec
## [1] "integer"
##
## $mean_recency_amount
## [1] "difftime"
##
## $median_recency_amount
## [1] "difftime"
##
## $mean_count_recency
## [1] "integer"
#change all difftime columns to class numeric
per_agency_category_rec$max_rec <-
as.numeric(per_agency_category_rec$max_rec, units = "days")
per_agency_category_rec$mean_rec <-
as.numeric(per_agency_category_rec$mean_rec, units = "days")
per_agency_category_rec$median_rec <-
as.numeric(per_agency_category_rec$median_rec, units = "days")
per_agency_category_rec$mean_recency_amount <-
as.numeric(per_agency_category_rec$mean_recency_amount, units = "days")
per_agency_category_rec$median_recency_amount <-
as.numeric(per_agency_category_rec$median_recency_amount, units = "days")
#add ratios to per_agency_category_rec
per_agency_category_rec <- per_agency_category_rec %>%
mutate(
max_rec_ratio = max_rec / mean_recency_amount,
mean_rec_ratio = mean_rec / mean_recency_amount,
median_rec_ratio = median_rec / median_recency_amount,
mean_rec_ratio = count_rec / mean_count_recency
) %>%
select(
-mean_recency_amount,
-median_recency_amount,
-mean_count_recency,-max_rec,
-mean_rec,
-median_rec,
-count_rec
) %>%
top_n(-4) # Use top_n(xx) to select the top xx rows, and top_n(-xx) for the bottom xx rows
#remove INF from median_rec_ratio
per_agency_category_rec <-
per_agency_category_rec[is.finite(per_agency_category_rec$median_rec_ratio),]
#create new DF, add MaxR to year_month column
max_per_agency_categor_rec <- per_agency_category_rec %>%
mutate(Year_Month = paste("MaxR", Year_Month, sep = "_")) %>%
select(-mean_rec_ratio,-median_rec_ratio)
#view head of max_per_agency_category_rec
kable(head(max_per_agency_categor_rec)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | max_rec_ratio |
|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> MaxR_201307 </td> <td style="text-align:right;"> 0.2135922 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | MaxR_201308 | 0.3883495 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> MaxR_201401 </td> <td style="text-align:right;"> 3.3592233 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | MaxR_201307 | 2.9473684 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:left;"> MaxR_201309 </td> <td style="text-align:right;"> 3.3684211 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | MaxR_201310 | 4.6315789 |
#create new DF, add MedR to year_month column
med_per_agency_category_rec <- per_agency_category_rec %>%
mutate(Year_Month = paste("MedR", Year_Month, sep = "_")) %>%
select(-mean_rec_ratio,-max_rec_ratio)
#view head of med_per_agency_category_rec
kable(head(med_per_agency_category_rec)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | median_rec_ratio |
|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> MedR_201307 </td> <td style="text-align:right;"> 0.4193548 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | MedR_201308 | 1.2903226 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> MedR_201401 </td> <td style="text-align:right;"> 11.1612903 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | MedR_201307 | 2.0000000 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:left;"> MedR_201309 </td> <td style="text-align:right;"> 0.0000000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | MedR_201310 | 2.0000000 |
#create new DF, add MeanR to year_month column
mean_per_agency_category_rec <- per_agency_category_rec %>%
mutate(Year_Month = paste("MeanR", Year_Month, sep = "_")) %>%
select(-median_rec_ratio,-max_rec_ratio)
#view head of mean_per_agency_category_rec
kable(head(mean_per_agency_category_rec)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Year_Month | mean_rec_ratio |
|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> MeanR_201307 </td> <td style="text-align:right;"> 0.5000000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
ADVERTISING SERVICES | MeanR_201308 | 0.2500000 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> MeanR_201401 </td> <td style="text-align:right;"> 0.2500000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | MeanR_201307 | 0.1250000 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> AMERICAN AIRLINES </td> <td style="text-align:left;"> MeanR_201309 </td> <td style="text-align:right;"> 0.2500000 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | MeanR_201310 | 0.2727273 |
#Max Recency variable: Use "dcast" in Library "reshape2" to organize the data
#so each row is a merchant category of an agent.
max_wide_rec <-
dcast(max_per_agency_categor_rec,
Agency_Name + Merchant_Category ~ Year_Month)
max_wide_rec = as.matrix(max_wide_rec)
max_wide_rec[is.na(max_wide_rec)] <- 0
max_wide_rec = as.data.frame(max_wide_rec)
#view head
kable(head(max_wide_rec)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | MaxR_201307 | MaxR_201308 | MaxR_201309 | MaxR_201310 | MaxR_201311 | MaxR_201312 | MaxR_201401 | MaxR_201402 | MaxR_201403 | MaxR_201404 | MaxR_201405 | MaxR_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 0.21359223 </td> <td style="text-align:left;"> 0.38834951 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 3.35922330 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 2.94736842 | 0 | 3.368421053 | 4.631578947 | 6.31578947 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOK STORES </td> <td style="text-align:left;"> 2.00000000 </td> <td style="text-align:left;"> 0.61538462 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 4.769230769 </td> <td style="text-align:left;"> 1.23076923 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 0 | 2.04878049 | 1.365853659 | 0 | 0 | 2.66341463 | 0.95609756 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> CATALOG MERCHANTS </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.595505618 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
CHARITABLE AND SOCIAL SERVICE ORGANIZATIONS | 0 | 1.95348837 | 1.395348837 | 2.372093023 | 0 | 5.44186047 | 0 | 0 | 0 | 0 | 0 | 0 |
# Median Recency variable: Use "dcast" in Library "reshape2" to organize the
#data so each row is a merchant category of an agent.
med_wide_rec <-
dcast(med_per_agency_category_rec,
Agency_Name + Merchant_Category ~ Year_Month)
med_wide_rec = as.matrix(med_wide_rec)
med_wide_rec[is.na(med_wide_rec)] <- 0
med_wide_rec = as.data.frame(med_wide_rec)
#view head
kable(head(med_wide_rec)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | MedR_201307 | MedR_201308 | MedR_201309 | MedR_201310 | MedR_201311 | MedR_201312 | MedR_201401 | MedR_201402 | MedR_201403 | MedR_201404 | MedR_201405 | MedR_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 0.41935484 </td> <td style="text-align:left;"> 1.29032258 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 11.16129032 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 2.00000000 | 0 | 0.000000000 | 2.000000000 | 0.00000000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOK STORES </td> <td style="text-align:left;"> 7.00000000 </td> <td style="text-align:left;"> 4.00000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 4.000000000 </td> <td style="text-align:left;"> 0.00000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 0 | 1.77777778 | 0.555555556 | 0 | 0 | 2.33333333 | 1.11111111 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> CATALOG MERCHANTS </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.000000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
CHARITABLE AND SOCIAL SERVICE ORGANIZATIONS | 0 | 0.50000000 | 1.000000000 | 1.000000000 | 0 | 1.25000000 | 0 | 0 | 0 | 0 | 0 | 0 |
# Mean Recency variable: Use "dcast" in Library "reshape2" to organize the
#data so each row is a merchant category of an agent.
mean_wide_rec <-
dcast(mean_per_agency_category_rec,
Agency_Name + Merchant_Category ~ Year_Month)
mean_wide_rec = as.matrix(mean_wide_rec)
mean_wide_rec[is.na(mean_wide_rec)] <- 0
mean_wide_rec = as.data.frame(mean_wide_rec)
#view head
kable(head(mean_wide_rec)) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | MeanR_201307 | MeanR_201308 | MeanR_201309 | MeanR_201310 | MeanR_201311 | MeanR_201312 | MeanR_201401 | MeanR_201402 | MeanR_201403 | MeanR_201404 | MeanR_201405 | MeanR_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> ADVERTISING SERVICES </td> <td style="text-align:left;"> 0.50000000 </td> <td style="text-align:left;"> 0.25000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0.25000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
AMERICAN AIRLINES | 0.12500000 | 0 | 0.25000000 | 0.27272727 | 0.15909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> BOOK STORES </td> <td style="text-align:left;"> 0.14285714 </td> <td style="text-align:left;"> 0.03571429 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0.17857143 </td> <td style="text-align:left;"> 0.53571429 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED | 0 | 0.21428571 | 0.35714286 | 0 | 0 | 0.14285714 | 0.21428571 | 0 | 0 | 0 | 0 | 0 |
DEPARTMENT OF EDUCATION </td> <td style="text-align:left;"> CATALOG MERCHANTS </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1.00000000 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 0 </td> </tr> <tr> <td style="text-align:left;">DEPARTMENT OF EDUCATION
|
CHARITABLE AND SOCIAL SERVICE ORGANIZATIONS | 0 | 0.33333333 | 0.25000000 | 0.25000000 | 0 | 0.12500000 | 0 | 0 | 0 | 0 | 0 | 0 |
#merge dataframes
model_df_rec <-
left_join(max_wide_rec,
mean_wide_rec,
by = c('Agency_Name', 'Merchant_Category'))
model_df_rec <-
merge(model_df_rec,
med_wide_rec,
by = c("Agency_Name", "Merchant_Category"))
#merge recency and transaction amount dataframes
model_df <-
merge(model_df_amt,
model_df_rec,
by = c("Agency_Name", "Merchant_Category"))
#View in excel, write to CSV
#write_csv(model_df, "model_df.csv")
#remove identifier columns
#model_df$Agency_Name <- NULL
#model_df$Merchant_Category <- NULL
#change ratio columns to numeric
cols = c(3:74)
model_df[, cols] = apply(model_df[, cols], 2, function(x)
as.numeric(as.character(x)))
#scale data
model_df_scale <- as.data.frame(scale(model_df[, cols]))
#remove mean ratio calculations, use median as a feature instead as
#it is not impacted by outliers.
to.remove <-
c(
"Mean_201307",
"Mean_201308",
"Mean_201309",
"Mean_201310",
"Mean_201311",
"Mean_201312",
"Mean_201401",
"Mean_201402",
"Mean_201403",
"Mean_201404",
"Mean_201405",
"Mean_201406",
"MeanR_201307",
"MeanR_201308",
"MeanR_201309",
"MeanR_201310",
"MeanR_201311",
"MeanR_201312",
"MeanR_201401",
"MeanR_201402",
"MeanR_201403",
"MeanR_201404",
"MeanR_201405",
"MeanR_201406"
)
`%ni%` <- Negate(`%in%`)
model_df_scale <-
subset(model_df_scale, select = names(model_df_scale) %ni% to.remove)
DBSCAN is a density based clustering algorithm. Unlike K-means, which makes round clusters, DBSCAN can handle clusters of various shapes and sizes. It is therefore able to find clusters that K-means is unable to discover. For fraud analysis, DBSCAN will group together points that are closely packed together and mark outlier points that lie outside these clusters. These outlier points could be possible fraudulent transactions.
Hyperparameters tuned include:
minPts - how many neighbors a point should have to be included into a cluster
eps (epsilon) - how close points should be to each other to be considered a part of a cluster
#load library
library(dbscan)
library(fpc)
library(factoextra)
library(rattle.data)
#principal component anlaysis to reduce high-dimensional data to two dimensions
fraud_PCA <- prcomp(model_df_scale)
fraud_PCA2 <- fraud_PCA$x[, 1:2]
#view head of ccard
kable(head(fraud_PCA2))
| PC1 | PC2 |
|---|---|
| 0.6956969 | 0.2121071 |
| -4.1154660 | 0.1033287 |
| -5.1863068 | 0.3878899 |
| -0.3590404 | 0.1282656 |
| 1.2587429 | 0.1550933 |
| -1.5495084 | 0.0768009 |
#Compute DBSCAN using fpc package
#minPts
#The rule of thumb for minPts is to use at least the number of dimensions of the data set plus one.
#(source: https://cran.r-project.org/web/packages/dbscan/vignettes/dbscan.pdf)
#In our case, this is 3. However, I tested other MinPts as well.
#I tested 3, 5, 20, 50 and 100.
#eps
#For eps, we can plot the points’ kNN distances (i.e., the distance to the kth nearest neighbor)
#in decreasing order and look for a knee in the plot.
#(source: https://cran.r-project.org/web/packages/dbscan/vignettes/dbscan.pdf)
#minPts = 3
kNNdistplot(model_df_scale, k = 3)
abline(h = 12, col = "red", lty = 2) #EPS = 12
#minPts = 5
kNNdistplot(model_df_scale, k = 5)
abline(h = 12, col = "red", lty = 2) #EPS = 12
#minPts = 20
kNNdistplot(model_df_scale, k = 20)
abline(h = 15, col = "red", lty = 2) #EPS = 15
#minPts = 50
kNNdistplot(model_df_scale, k = 50)
abline(h = 15, col = "red", lty = 2) #EPS = 15
#minPts = 100
kNNdistplot(model_df_scale, k = 100)
abline(h = 15, col = "red", lty = 2) #EPS = 15
#eps = 12, MinPts = 3
set.seed(1)
modl <- fpc::dbscan(model_df_scale, eps = 12, MinPts = 3)
#view table
modl #The clustering contains 3 clusters and 52 noise points.
## dbscan Pts=5471 MinPts=3 eps=12
## 0 1 2 3
## border 52 10 0 0
## seed 0 5401 3 5
## total 52 5411 3 5
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = 12, MinPts = 3",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl$cluster
)
points(fraud_PCA2[modl$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl$cluster == 0,]
#eps = 12, MinPts = 5
set.seed(1)
modl2 <- fpc::dbscan(model_df_scale, eps = 12, MinPts = 5)
#view table
modl2 #The clustering contains 2 clusters and 58 noise points.
## dbscan Pts=5471 MinPts=5 eps=12
## 0 1 2
## border 58 25 0
## seed 0 5383 5
## total 58 5408 5
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = 12, MinPts = 5",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl2$cluster
)
points(fraud_PCA2[modl2$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl2$cluster == 0,]
#eps = 15, MinPts = 20
set.seed(1)
modl2b <- fpc::dbscan(model_df_scale, eps = 15, MinPts = 20)
#view table
modl2b #The clustering contains 1 cluster and 44 noise points.
## dbscan Pts=5471 MinPts=20 eps=15
## 0 1
## border 44 44
## seed 0 5383
## total 44 5427
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = 15, MinPts = 20",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl2b$cluster
)
points(fraud_PCA2[modl2b$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl2b$cluster == 0,]
#eps = 15, MinPts = 50
set.seed(1)
modl3 <- fpc::dbscan(model_df_scale, eps = 15, MinPts = 50)
#view table
modl3 #The clustering contains 1 cluster and 46 noise points.
## dbscan Pts=5471 MinPts=50 eps=15
## 0 1
## border 46 57
## seed 0 5368
## total 46 5425
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = 15, MinPts = 50",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl3$cluster
)
points(fraud_PCA2[modl3$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl3$cluster == 0,]
#eps = 15, MinPts = 100
set.seed(1)
modl4 <- fpc::dbscan(model_df_scale, eps = 15, MinPts = 100)
#view table
modl4 #The clustering contains 1 cluster and 46 noise points.
## dbscan Pts=5471 MinPts=100 eps=15
## 0 1
## border 46 67
## seed 0 5358
## total 46 5425
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = 15, MinPts = 100",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl4$cluster
)
points(fraud_PCA2[modl4$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl4$cluster == 0,]
#I also tested smaller numbers for EPS - 0.01, 0.15, 0.5, 0.99, 2.0
#eps = .01, MinPts = 50
set.seed(1)
modl5 <- fpc::dbscan(model_df_scale, eps = 0.01, MinPts = 50)
#view table
modl5 #The clustering contains 0 clusters and 5471 noise points, not useful.
## dbscan Pts=5471 MinPts=50 eps=0.01
##
## 0
## 5471
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = .01, MinPts = 50",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl5$cluster
)
points(fraud_PCA2[modl5$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl5$cluster == 0,]
#eps = 0.15, MinPts = 50
set.seed(1)
modl6 <- fpc::dbscan(model_df_scale, eps = 0.15, MinPts = 50)
#view table
modl6 #The clustering contains 0 clusters and 5471 noise points, not useful.
## dbscan Pts=5471 MinPts=50 eps=0.15
##
## 0
## 5471
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = .15, MinPts = 50",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl6$cluster
)
points(fraud_PCA2[modl6$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl6$cluster == 0,]
#eps = 0.5, MinPts = 50
set.seed(1)
modl7 <- fpc::dbscan(model_df_scale, eps = 0.5, MinPts = 50)
#view table
modl7 #The clustering contains 3 clusters and 5265 noise points, not useful.
## dbscan Pts=5471 MinPts=50 eps=0.5
## 0 1 2 3
## border 5265 41 60 51
## seed 0 26 16 12
## total 5265 67 76 63
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = .5, MinPts = 50",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl7$cluster
)
points(fraud_PCA2[modl7$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl7$cluster == 0,]
#eps = 0.99, MinPts = 50
set.seed(1)
modl8 <- fpc::dbscan(model_df_scale, eps = 0.99, MinPts = 50)
#view table
modl8 #The clustering contains 8 clusters and 4289 noise points, not useful.
## dbscan Pts=5471 MinPts=50 eps=0.99
## 0 1 2 3 4 5 6 7 8
## border 4289 35 48 42 37 101 122 39 50
## seed 0 43 46 77 27 146 232 57 80
## total 4289 78 94 119 64 247 354 96 130
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = .5, MinPts = 50",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl8$cluster
)
points(fraud_PCA2[modl8$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl8$cluster == 0,]
#eps = 2, MinPts = 50
set.seed(1)
modl9 <- fpc::dbscan(model_df_scale, eps = 2, MinPts = 50)
#view table
modl9 #The clustering contains 1 cluster1 and 2633 noise points, not useful.
## dbscan Pts=5471 MinPts=50 eps=2
## 0 1
## border 2633 827
## seed 0 2011
## total 2633 2838
#plot clusters and add noise (cluster 0) as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters\neps = 2, MinPts = 50",
sub = "Noise points plotted as crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red",
col =
modl9$cluster
)
points(fraud_PCA2[modl9$cluster == 0,], pch = 3, col = "red")
noise <- model_df[modl9$cluster == 0,]
It appears that using eps of 15 and MinPts of 50 resulted in a reasonable model. It clustered the data points into 1 cluster with 46 outliers.
modl3 #The clustering contains 1 cluster and 46 noise points.
## dbscan Pts=5471 MinPts=50 eps=15
## 0 1
## border 46 57
## seed 0 5368
## total 46 5425
#plot clusters and add noise (cluster 0) as crosses.
plot(fraud_PCA2, main = "Credit Card Transaction Clusters\neps = 15, MinPts = 50", sub = "Noise points plotted as crosses", cex.sub = 0.75, font.sub = 3, col.sub = "red", col =
modl3$cluster)
points(fraud_PCA2[modl3$cluster == 0, ], pch = 3, col = "red")
noise <- model_df[modl3$cluster == 0, ]
#create DF that include possible fraud transactions
fraud <- model_df[modl3$cluster == 0, ]
fraud <- fraud[, 1:2]
#view fraud
kable(fraud) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | |
|---|---|---|
| 35 | ARDMORE HIGHER EDUCATION CENTER | HOUSEHOLD APPLIANCE STORES |
| 279 | COMM. ON CONSUMER CREDIT | GOVERNMENT SERVICES–NOT ELSEWHERE CLASSIFIED |
| 293 | COMM. ON CONSUMER CREDIT | SHERATON |
| 327 | COMPSOURCE OKLAHOMA | DELTA |
| 1301 | DEPARTMENT OF REHABILITATION SERVICES | GOVERNMENT SERVICES–NOT ELSEWHERE CLASSIFIED |
| 1328 | DEPARTMENT OF REHABILITATION SERVICES | MISCELLANEOUS FOOD STORES-CONV STRS AND SPECIALTY MKTS. |
| 1462 | DEPARTMENT OF TOURISM AND RECREATION | MISCELLANEOUS AND SPECIALTY RETAIL STORES |
| 1495 | DEPARTMENT OF TOURISM AND RECREATION | SHERATON |
| 1542 | DEPARTMENT OF TRANSPORTATION | COMMERCIAL EQUIPMENT, NOT ELSEWHERE CLASSIFIED |
| 1721 | DEPARTMENT OF VETERANS AFFAIRS | MARRIOTT |
| 1826 | DEPARTMENT OF WILDLIFE CONSERVATION | HILTON HOTELS |
| 2159 | GRAND RIVER DAM AUTH. | COMMERCIAL EQUIPMENT, NOT ELSEWHERE CLASSIFIED |
| 2165 | GRAND RIVER DAM AUTH. | COMPUTERS, COMPUTER PERIPHERAL EQUIPMENT, SOFTWARE |
| 2174 | GRAND RIVER DAM AUTH. | DETECTIVE AGENCIES,PROTECTIVE AGENCIES,AND SECURITY SERVICES |
| 2182 | GRAND RIVER DAM AUTH. | EMPLOYMENT AGENCIES AND TEMPORARY HELP SERVICES |
| 2194 | GRAND RIVER DAM AUTH. | GOVERNMENT SERVICES–NOT ELSEWHERE CLASSIFIED |
| 2203 | GRAND RIVER DAM AUTH. | HOMEWOOD SUITES |
| 2260 | GRAND RIVER DAM AUTH. | TELECOMMUNICATION EQUIPMENT AND TELEPHONE SALES |
| 2614 | MENTAL HEALTH AND SUBSTANCE ABUSE SERV. | DEPARTMENT STORES |
| 2687 | MENTAL HEALTH AND SUBSTANCE ABUSE SERV. | RENAISSANCE HOTELS |
| 2713 | N. E. OKLA. A & M COLLEGE | AUTOMATED FUEL DISPENSER |
| 2752 | N. E. OKLA. A & M COLLEGE | RECORD STORES |
| 2782 | OFFICE OF JUVENILE AFFAIRS | COMFORT HOTEL INTERNATIONAL |
| 2865 | OFFICE OF MANAGEMENT AND ENTERPRISE SERV | BUSINESS SERVICES NOT ELSEWHERE CLASSIFIED |
| 2880 | OFFICE OF MANAGEMENT AND ENTERPRISE SERV | COMMERCIAL EQUIPMENT, NOT ELSEWHERE CLASSIFIED |
| 2975 | OFFICE OF MANAGEMENT AND ENTERPRISE SERV | TOLLS AND BRIDGE FEES |
| 3330 | OKLA. CITY COMMUNITY COLLEGE | GROCERY STORES,AND SUPERMARKETS |
| 3374 | OKLA. HORSE RACING COMM. | GOVERNMENT SERVICES–NOT ELSEWHERE CLASSIFIED |
| 3471 | OKLA. PANHANDLE STATE UNIV. | MOTOR FREIGHT CARRIERS,AND TRUCKING |
| 3485 | OKLA. PANHANDLE STATE UNIV. | RECORD STORES |
| 3572 | OKLAHOMA AERONAUTICS COMMISSION | COMP PROG,DATA PROCESSING,AND INTEGRATED SYS DES IGN SVCS |
| 3821 | OKLAHOMA STATE UNIVERSITY | AIRLINES AND AIR CARRIERS |
| 3937 | OKLAHOMA STATE UNIVERSITY | LOCAL AND SUBURBAN COMMUTER PASS TRANS, INCLUDING FEE |
| 3988 | OKLAHOMA STATE UNIVERSITY | RECORD STORES |
| 4022 | OKLAHOMA STATE UNIVERSITY | VARIETY STORES |
| 4143 | REDLANDS COMMUNITY COLLEGE | COLLEGES,UNIVERSITIES,PROFESSIONAL SCHLS AND JR COLLEGES |
| 4165 | REDLANDS COMMUNITY COLLEGE | LUXOR HOTEL AND CASINO |
| 4450 | SECRETARY OF STATE | TRAVEL AGENCIES |
| 4699 | STATE DEPARTMENT OF HEALTH | HYATT PLACE |
| 4713 | STATE DEPARTMENT OF HEALTH | MISCELLANEOUS GENERAL MERCHANDISE |
| 4717 | STATE DEPARTMENT OF HEALTH | NON-DURABLE GOODS NOT ELSEWHERE CLASSIFIED |
| 4752 | STATE ELECTION BOARD | STATIONERY,OFFICE AND SCHOOL SUPPLY STORES |
| 4993 | TULSA COMMUNITY COLLEGE | NON-DURABLE GOODS NOT ELSEWHERE CLASSIFIED |
| 5156 | UNIV.OF SCIENCE & ARTS OF OK | COMFORT HOTEL INTERNATIONAL |
| 5169 | UNIV.OF SCIENCE & ARTS OF OK | FAST FOOD RESTAURANTS |
| 5239 | UNIVERSITY OF OKLAHOMA | CAMPER,RECREATIONAL AND UTILITY TRAILER DEALERS |
Agency transactions that occurred within the merchant category listed in the fraud data frame could possibly be fraud based on my DBSCAN analysis. Transactions that occurred within these merchant categories at these agencies require further analysis to determine if fraud actually occurred.
The mean shift algorithm is a non parametric clustering technique. It can handle clusters of various shapes and sizes and prior knowledge of the number of clusters is not required. For each data point, mean shift defines a window around it and computes the mean of the data point. It then shifts the center of the window towards the mean and repeats the algorithm until it converges. For fraud analysis, data points far from the centroids can be ignored by the clustering process and flagged as anomalies. These anomaly points could be possible fraudulent transactions.
Hyperparameter tuned include: h: a positive bandwidth parameter. Larger values of h produce few and large clusters. Smaller values of h produce many small clusters.
I analyzed h values of: 10, 20, 30, 50 and 75.
#load library
library(MeanShift)
library(ggfortify)
#view dimension of model_df_scale
dim(model_df_scale)
## [1] 5471 48
#transpose data
model_df_trans <- t(model_df_scale)
#view dimension of model_df_trans
dim(model_df_trans)
## [1] 48 5471
#view head of model_df_trans
kable(head(model_df_trans))
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 110 | 111 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 230 | 231 | 232 | 233 | 234 | 235 | 236 | 237 | 238 | 239 | 240 | 241 | 242 | 243 | 244 | 245 | 246 | 247 | 248 | 249 | 250 | 251 | 252 | 253 | 254 | 255 | 256 | 257 | 258 | 259 | 260 | 261 | 262 | 263 | 264 | 265 | 266 | 267 | 268 | 269 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 278 | 279 | 280 | 281 | 282 | 283 | 284 | 285 | 286 | 287 | 288 | 289 | 290 | 291 | 292 | 293 | 294 | 295 | 296 | 297 | 298 | 299 | 300 | 301 | 302 | 303 | 304 | 305 | 306 | 307 | 308 | 309 | 310 | 311 | 312 | 313 | 314 | 315 | 316 | 317 | 318 | 319 | 320 | 321 | 322 | 323 | 324 | 325 | 326 | 327 | 328 | 329 | 330 | 331 | 332 | 333 | 334 | 335 | 336 | 337 | 338 | 339 | 340 | 341 | 342 | 343 | 344 | 345 | 346 | 347 | 348 | 349 | 350 | 351 | 352 | 353 | 354 | 355 | 356 | 357 | 358 | 359 | 360 | 361 | 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | 370 | 371 | 372 | 373 | 374 | 375 | 376 | 377 | 378 | 379 | 380 | 381 | 382 | 383 | 384 | 385 | 386 | 387 | 388 | 389 | 390 | 391 | 392 | 393 | 394 | 395 | 396 | 397 | 398 | 399 | 400 | 401 | 402 | 403 | 404 | 405 | 406 | 407 | 408 | 409 | 410 | 411 | 412 | 413 | 414 | 415 | 416 | 417 | 418 | 419 | 420 | 421 | 422 | 423 | 424 | 425 | 426 | 427 | 428 | 429 | 430 | 431 | 432 | 433 | 434 | 435 | 436 | 437 | 438 | 439 | 440 | 441 | 442 | 443 | 444 | 445 | 446 | 447 | 448 | 449 | 450 | 451 | 452 | 453 | 454 | 455 | 456 | 457 | 458 | 459 | 460 | 461 | 462 | 463 | 464 | 465 | 466 | 467 | 468 | 469 | 470 | 471 | 472 | 473 | 474 | 475 | 476 | 477 | 478 | 479 | 480 | 481 | 482 | 483 | 484 | 485 | 486 | 487 | 488 | 489 | 490 | 491 | 492 | 493 | 494 | 495 | 496 | 497 | 498 | 499 | 500 | 501 | 502 | 503 | 504 | 505 | 506 | 507 | 508 | 509 | 510 | 511 | 512 | 513 | 514 | 515 | 516 | 517 | 518 | 519 | 520 | 521 | 522 | 523 | 524 | 525 | 526 | 527 | 528 | 529 | 530 | 531 | 532 | 533 | 534 | 535 | 536 | 537 | 538 | 539 | 540 | 541 | 542 | 543 | 544 | 545 | 546 | 547 | 548 | 549 | 550 | 551 | 552 | 553 | 554 | 555 | 556 | 557 | 558 | 559 | 560 | 561 | 562 | 563 | 564 | 565 | 566 | 567 | 568 | 569 | 570 | 571 | 572 | 573 | 574 | 575 | 576 | 577 | 578 | 579 | 580 | 581 | 582 | 583 | 584 | 585 | 586 | 587 | 588 | 589 | 590 | 591 | 592 | 593 | 594 | 595 | 596 | 597 | 598 | 599 | 600 | 601 | 602 | 603 | 604 | 605 | 606 | 607 | 608 | 609 | 610 | 611 | 612 | 613 | 614 | 615 | 616 | 617 | 618 | 619 | 620 | 621 | 622 | 623 | 624 | 625 | 626 | 627 | 628 | 629 | 630 | 631 | 632 | 633 | 634 | 635 | 636 | 637 | 638 | 639 | 640 | 641 | 642 | 643 | 644 | 645 | 646 | 647 | 648 | 649 | 650 | 651 | 652 | 653 | 654 | 655 | 656 | 657 | 658 | 659 | 660 | 661 | 662 | 663 | 664 | 665 | 666 | 667 | 668 | 669 | 670 | 671 | 672 | 673 | 674 | 675 | 676 | 677 | 678 | 679 | 680 | 681 | 682 | 683 | 684 | 685 | 686 | 687 | 688 | 689 | 690 | 691 | 692 | 693 | 694 | 695 | 696 | 697 | 698 | 699 | 700 | 701 | 702 | 703 | 704 | 705 | 706 | 707 | 708 | 709 | 710 | 711 | 712 | 713 | 714 | 715 | 716 | 717 | 718 | 719 | 720 | 721 | 722 | 723 | 724 | 725 | 726 | 727 | 728 | 729 | 730 | 731 | 732 | 733 | 734 | 735 | 736 | 737 | 738 | 739 | 740 | 741 | 742 | 743 | 744 | 745 | 746 | 747 | 748 | 749 | 750 | 751 | 752 | 753 | 754 | 755 | 756 | 757 | 758 | 759 | 760 | 761 | 762 | 763 | 764 | 765 | 766 | 767 | 768 | 769 | 770 | 771 | 772 | 773 | 774 | 775 | 776 | 777 | 778 | 779 | 780 | 781 | 782 | 783 | 784 | 785 | 786 | 787 | 788 | 789 | 790 | 791 | 792 | 793 | 794 | 795 | 796 | 797 | 798 | 799 | 800 | 801 | 802 | 803 | 804 | 805 | 806 | 807 | 808 | 809 | 810 | 811 | 812 | 813 | 814 | 815 | 816 | 817 | 818 | 819 | 820 | 821 | 822 | 823 | 824 | 825 | 826 | 827 | 828 | 829 | 830 | 831 | 832 | 833 | 834 | 835 | 836 | 837 | 838 | 839 | 840 | 841 | 842 | 843 | 844 | 845 | 846 | 847 | 848 | 849 | 850 | 851 | 852 | 853 | 854 | 855 | 856 | 857 | 858 | 859 | 860 | 861 | 862 | 863 | 864 | 865 | 866 | 867 | 868 | 869 | 870 | 871 | 872 | 873 | 874 | 875 | 876 | 877 | 878 | 879 | 880 | 881 | 882 | 883 | 884 | 885 | 886 | 887 | 888 | 889 | 890 | 891 | 892 | 893 | 894 | 895 | 896 | 897 | 898 | 899 | 900 | 901 | 902 | 903 | 904 | 905 | 906 | 907 | 908 | 909 | 910 | 911 | 912 | 913 | 914 | 915 | 916 | 917 | 918 | 919 | 920 | 921 | 922 | 923 | 924 | 925 | 926 | 927 | 928 | 929 | 930 | 931 | 932 | 933 | 934 | 935 | 936 | 937 | 938 | 939 | 940 | 941 | 942 | 943 | 944 | 945 | 946 | 947 | 948 | 949 | 950 | 951 | 952 | 953 | 954 | 955 | 956 | 957 | 958 | 959 | 960 | 961 | 962 | 963 | 964 | 965 | 966 | 967 | 968 | 969 | 970 | 971 | 972 | 973 | 974 | 975 | 976 | 977 | 978 | 979 | 980 | 981 | 982 | 983 | 984 | 985 | 986 | 987 | 988 | 989 | 990 | 991 | 992 | 993 | 994 | 995 | 996 | 997 | 998 | 999 | 1000 | 1001 | 1002 | 1003 | 1004 | 1005 | 1006 | 1007 | 1008 | 1009 | 1010 | 1011 | 1012 | 1013 | 1014 | 1015 | 1016 | 1017 | 1018 | 1019 | 1020 | 1021 | 1022 | 1023 | 1024 | 1025 | 1026 | 1027 | 1028 | 1029 | 1030 | 1031 | 1032 | 1033 | 1034 | 1035 | 1036 | 1037 | 1038 | 1039 | 1040 | 1041 | 1042 | 1043 | 1044 | 1045 | 1046 | 1047 | 1048 | 1049 | 1050 | 1051 | 1052 | 1053 | 1054 | 1055 | 1056 | 1057 | 1058 | 1059 | 1060 | 1061 | 1062 | 1063 | 1064 | 1065 | 1066 | 1067 | 1068 | 1069 | 1070 | 1071 | 1072 | 1073 | 1074 | 1075 | 1076 | 1077 | 1078 | 1079 | 1080 | 1081 | 1082 | 1083 | 1084 | 1085 | 1086 | 1087 | 1088 | 1089 | 1090 | 1091 | 1092 | 1093 | 1094 | 1095 | 1096 | 1097 | 1098 | 1099 | 1100 | 1101 | 1102 | 1103 | 1104 | 1105 | 1106 | 1107 | 1108 | 1109 | 1110 | 1111 | 1112 | 1113 | 1114 | 1115 | 1116 | 1117 | 1118 | 1119 | 1120 | 1121 | 1122 | 1123 | 1124 | 1125 | 1126 | 1127 | 1128 | 1129 | 1130 | 1131 | 1132 | 1133 | 1134 | 1135 | 1136 | 1137 | 1138 | 1139 | 1140 | 1141 | 1142 | 1143 | 1144 | 1145 | 1146 | 1147 | 1148 | 1149 | 1150 | 1151 | 1152 | 1153 | 1154 | 1155 | 1156 | 1157 | 1158 | 1159 | 1160 | 1161 | 1162 | 1163 | 1164 | 1165 | 1166 | 1167 | 1168 | 1169 | 1170 | 1171 | 1172 | 1173 | 1174 | 1175 | 1176 | 1177 | 1178 | 1179 | 1180 | 1181 | 1182 | 1183 | 1184 | 1185 | 1186 | 1187 | 1188 | 1189 | 1190 | 1191 | 1192 | 1193 | 1194 | 1195 | 1196 | 1197 | 1198 | 1199 | 1200 | 1201 | 1202 | 1203 | 1204 | 1205 | 1206 | 1207 | 1208 | 1209 | 1210 | 1211 | 1212 | 1213 | 1214 | 1215 | 1216 | 1217 | 1218 | 1219 | 1220 | 1221 | 1222 | 1223 | 1224 | 1225 | 1226 | 1227 | 1228 | 1229 | 1230 | 1231 | 1232 | 1233 | 1234 | 1235 | 1236 | 1237 | 1238 | 1239 | 1240 | 1241 | 1242 | 1243 | 1244 | 1245 | 1246 | 1247 | 1248 | 1249 | 1250 | 1251 | 1252 | 1253 | 1254 | 1255 | 1256 | 1257 | 1258 | 1259 | 1260 | 1261 | 1262 | 1263 | 1264 | 1265 | 1266 | 1267 | 1268 | 1269 | 1270 | 1271 | 1272 | 1273 | 1274 | 1275 | 1276 | 1277 | 1278 | 1279 | 1280 | 1281 | 1282 | 1283 | 1284 | 1285 | 1286 | 1287 | 1288 | 1289 | 1290 | 1291 | 1292 | 1293 | 1294 | 1295 | 1296 | 1297 | 1298 | 1299 | 1300 | 1301 | 1302 | 1303 | 1304 | 1305 | 1306 | 1307 | 1308 | 1309 | 1310 | 1311 | 1312 | 1313 | 1314 | 1315 | 1316 | 1317 | 1318 | 1319 | 1320 | 1321 | 1322 | 1323 | 1324 | 1325 | 1326 | 1327 | 1328 | 1329 | 1330 | 1331 | 1332 | 1333 | 1334 | 1335 | 1336 | 1337 | 1338 | 1339 | 1340 | 1341 | 1342 | 1343 | 1344 | 1345 | 1346 | 1347 | 1348 | 1349 | 1350 | 1351 | 1352 | 1353 | 1354 | 1355 | 1356 | 1357 | 1358 | 1359 | 1360 | 1361 | 1362 | 1363 | 1364 | 1365 | 1366 | 1367 | 1368 | 1369 | 1370 | 1371 | 1372 | 1373 | 1374 | 1375 | 1376 | 1377 | 1378 | 1379 | 1380 | 1381 | 1382 | 1383 | 1384 | 1385 | 1386 | 1387 | 1388 | 1389 | 1390 | 1391 | 1392 | 1393 | 1394 | 1395 | 1396 | 1397 | 1398 | 1399 | 1400 | 1401 | 1402 | 1403 | 1404 | 1405 | 1406 | 1407 | 1408 | 1409 | 1410 | 1411 | 1412 | 1413 | 1414 | 1415 | 1416 | 1417 | 1418 | 1419 | 1420 | 1421 | 1422 | 1423 | 1424 | 1425 | 1426 | 1427 | 1428 | 1429 | 1430 | 1431 | 1432 | 1433 | 1434 | 1435 | 1436 | 1437 | 1438 | 1439 | 1440 | 1441 | 1442 | 1443 | 1444 | 1445 | 1446 | 1447 | 1448 | 1449 | 1450 | 1451 | 1452 | 1453 | 1454 | 1455 | 1456 | 1457 | 1458 | 1459 | 1460 | 1461 | 1462 | 1463 | 1464 | 1465 | 1466 | 1467 | 1468 | 1469 | 1470 | 1471 | 1472 | 1473 | 1474 | 1475 | 1476 | 1477 | 1478 | 1479 | 1480 | 1481 | 1482 | 1483 | 1484 | 1485 | 1486 | 1487 | 1488 | 1489 | 1490 | 1491 | 1492 | 1493 | 1494 | 1495 | 1496 | 1497 | 1498 | 1499 | 1500 | 1501 | 1502 | 1503 | 1504 | 1505 | 1506 | 1507 | 1508 | 1509 | 1510 | 1511 | 1512 | 1513 | 1514 | 1515 | 1516 | 1517 | 1518 | 1519 | 1520 | 1521 | 1522 | 1523 | 1524 | 1525 | 1526 | 1527 | 1528 | 1529 | 1530 | 1531 | 1532 | 1533 | 1534 | 1535 | 1536 | 1537 | 1538 | 1539 | 1540 | 1541 | 1542 | 1543 | 1544 | 1545 | 1546 | 1547 | 1548 | 1549 | 1550 | 1551 | 1552 | 1553 | 1554 | 1555 | 1556 | 1557 | 1558 | 1559 | 1560 | 1561 | 1562 | 1563 | 1564 | 1565 | 1566 | 1567 | 1568 | 1569 | 1570 | 1571 | 1572 | 1573 | 1574 | 1575 | 1576 | 1577 | 1578 | 1579 | 1580 | 1581 | 1582 | 1583 | 1584 | 1585 | 1586 | 1587 | 1588 | 1589 | 1590 | 1591 | 1592 | 1593 | 1594 | 1595 | 1596 | 1597 | 1598 | 1599 | 1600 | 1601 | 1602 | 1603 | 1604 | 1605 | 1606 | 1607 | 1608 | 1609 | 1610 | 1611 | 1612 | 1613 | 1614 | 1615 | 1616 | 1617 | 1618 | 1619 | 1620 | 1621 | 1622 | 1623 | 1624 | 1625 | 1626 | 1627 | 1628 | 1629 | 1630 | 1631 | 1632 | 1633 | 1634 | 1635 | 1636 | 1637 | 1638 | 1639 | 1640 | 1641 | 1642 | 1643 | 1644 | 1645 | 1646 | 1647 | 1648 | 1649 | 1650 | 1651 | 1652 | 1653 | 1654 | 1655 | 1656 | 1657 | 1658 | 1659 | 1660 | 1661 | 1662 | 1663 | 1664 | 1665 | 1666 | 1667 | 1668 | 1669 | 1670 | 1671 | 1672 | 1673 | 1674 | 1675 | 1676 | 1677 | 1678 | 1679 | 1680 | 1681 | 1682 | 1683 | 1684 | 1685 | 1686 | 1687 | 1688 | 1689 | 1690 | 1691 | 1692 | 1693 | 1694 | 1695 | 1696 | 1697 | 1698 | 1699 | 1700 | 1701 | 1702 | 1703 | 1704 | 1705 | 1706 | 1707 | 1708 | 1709 | 1710 | 1711 | 1712 | 1713 | 1714 | 1715 | 1716 | 1717 | 1718 | 1719 | 1720 | 1721 | 1722 | 1723 | 1724 | 1725 | 1726 | 1727 | 1728 | 1729 | 1730 | 1731 | 1732 | 1733 | 1734 | 1735 | 1736 | 1737 | 1738 | 1739 | 1740 | 1741 | 1742 | 1743 | 1744 | 1745 | 1746 | 1747 | 1748 | 1749 | 1750 | 1751 | 1752 | 1753 | 1754 | 1755 | 1756 | 1757 | 1758 | 1759 | 1760 | 1761 | 1762 | 1763 | 1764 | 1765 | 1766 | 1767 | 1768 | 1769 | 1770 | 1771 | 1772 | 1773 | 1774 | 1775 | 1776 | 1777 | 1778 | 1779 | 1780 | 1781 | 1782 | 1783 | 1784 | 1785 | 1786 | 1787 | 1788 | 1789 | 1790 | 1791 | 1792 | 1793 | 1794 | 1795 | 1796 | 1797 | 1798 | 1799 | 1800 | 1801 | 1802 | 1803 | 1804 | 1805 | 1806 | 1807 | 1808 | 1809 | 1810 | 1811 | 1812 | 1813 | 1814 | 1815 | 1816 | 1817 | 1818 | 1819 | 1820 | 1821 | 1822 | 1823 | 1824 | 1825 | 1826 | 1827 | 1828 | 1829 | 1830 | 1831 | 1832 | 1833 | 1834 | 1835 | 1836 | 1837 | 1838 | 1839 | 1840 | 1841 | 1842 | 1843 | 1844 | 1845 | 1846 | 1847 | 1848 | 1849 | 1850 | 1851 | 1852 | 1853 | 1854 | 1855 | 1856 | 1857 | 1858 | 1859 | 1860 | 1861 | 1862 | 1863 | 1864 | 1865 | 1866 | 1867 | 1868 | 1869 | 1870 | 1871 | 1872 | 1873 | 1874 | 1875 | 1876 | 1877 | 1878 | 1879 | 1880 | 1881 | 1882 | 1883 | 1884 | 1885 | 1886 | 1887 | 1888 | 1889 | 1890 | 1891 | 1892 | 1893 | 1894 | 1895 | 1896 | 1897 | 1898 | 1899 | 1900 | 1901 | 1902 | 1903 | 1904 | 1905 | 1906 | 1907 | 1908 | 1909 | 1910 | 1911 | 1912 | 1913 | 1914 | 1915 | 1916 | 1917 | 1918 | 1919 | 1920 | 1921 | 1922 | 1923 | 1924 | 1925 | 1926 | 1927 | 1928 | 1929 | 1930 | 1931 | 1932 | 1933 | 1934 | 1935 | 1936 | 1937 | 1938 | 1939 | 1940 | 1941 | 1942 | 1943 | 1944 | 1945 | 1946 | 1947 | 1948 | 1949 | 1950 | 1951 | 1952 | 1953 | 1954 | 1955 | 1956 | 1957 | 1958 | 1959 | 1960 | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 | 2029 | 2030 | 2031 | 2032 | 2033 | 2034 | 2035 | 2036 | 2037 | 2038 | 2039 | 2040 | 2041 | 2042 | 2043 | 2044 | 2045 | 2046 | 2047 | 2048 | 2049 | 2050 | 2051 | 2052 | 2053 | 2054 | 2055 | 2056 | 2057 | 2058 | 2059 | 2060 | 2061 | 2062 | 2063 | 2064 | 2065 | 2066 | 2067 | 2068 | 2069 | 2070 | 2071 | 2072 | 2073 | 2074 | 2075 | 2076 | 2077 | 2078 | 2079 | 2080 | 2081 | 2082 | 2083 | 2084 | 2085 | 2086 | 2087 | 2088 | 2089 | 2090 | 2091 | 2092 | 2093 | 2094 | 2095 | 2096 | 2097 | 2098 | 2099 | 2100 | 2101 | 2102 | 2103 | 2104 | 2105 | 2106 | 2107 | 2108 | 2109 | 2110 | 2111 | 2112 | 2113 | 2114 | 2115 | 2116 | 2117 | 2118 | 2119 | 2120 | 2121 | 2122 | 2123 | 2124 | 2125 | 2126 | 2127 | 2128 | 2129 | 2130 | 2131 | 2132 | 2133 | 2134 | 2135 | 2136 | 2137 | 2138 | 2139 | 2140 | 2141 | 2142 | 2143 | 2144 | 2145 | 2146 | 2147 | 2148 | 2149 | 2150 | 2151 | 2152 | 2153 | 2154 | 2155 | 2156 | 2157 | 2158 | 2159 | 2160 | 2161 | 2162 | 2163 | 2164 | 2165 | 2166 | 2167 | 2168 | 2169 | 2170 | 2171 | 2172 | 2173 | 2174 | 2175 | 2176 | 2177 | 2178 | 2179 | 2180 | 2181 | 2182 | 2183 | 2184 | 2185 | 2186 | 2187 | 2188 | 2189 | 2190 | 2191 | 2192 | 2193 | 2194 | 2195 | 2196 | 2197 | 2198 | 2199 | 2200 | 2201 | 2202 | 2203 | 2204 | 2205 | 2206 | 2207 | 2208 | 2209 | 2210 | 2211 | 2212 | 2213 | 2214 | 2215 | 2216 | 2217 | 2218 | 2219 | 2220 | 2221 | 2222 | 2223 | 2224 | 2225 | 2226 | 2227 | 2228 | 2229 | 2230 | 2231 | 2232 | 2233 | 2234 | 2235 | 2236 | 2237 | 2238 | 2239 | 2240 | 2241 | 2242 | 2243 | 2244 | 2245 | 2246 | 2247 | 2248 | 2249 | 2250 | 2251 | 2252 | 2253 | 2254 | 2255 | 2256 | 2257 | 2258 | 2259 | 2260 | 2261 | 2262 | 2263 | 2264 | 2265 | 2266 | 2267 | 2268 | 2269 | 2270 | 2271 | 2272 | 2273 | 2274 | 2275 | 2276 | 2277 | 2278 | 2279 | 2280 | 2281 | 2282 | 2283 | 2284 | 2285 | 2286 | 2287 | 2288 | 2289 | 2290 | 2291 | 2292 | 2293 | 2294 | 2295 | 2296 | 2297 | 2298 | 2299 | 2300 | 2301 | 2302 | 2303 | 2304 | 2305 | 2306 | 2307 | 2308 | 2309 | 2310 | 2311 | 2312 | 2313 | 2314 | 2315 | 2316 | 2317 | 2318 | 2319 | 2320 | 2321 | 2322 | 2323 | 2324 | 2325 | 2326 | 2327 | 2328 | 2329 | 2330 | 2331 | 2332 | 2333 | 2334 | 2335 | 2336 | 2337 | 2338 | 2339 | 2340 | 2341 | 2342 | 2343 | 2344 | 2345 | 2346 | 2347 | 2348 | 2349 | 2350 | 2351 | 2352 | 2353 | 2354 | 2355 | 2356 | 2357 | 2358 | 2359 | 2360 | 2361 | 2362 | 2363 | 2364 | 2365 | 2366 | 2367 | 2368 | 2369 | 2370 | 2371 | 2372 | 2373 | 2374 | 2375 | 2376 | 2377 | 2378 | 2379 | 2380 | 2381 | 2382 | 2383 | 2384 | 2385 | 2386 | 2387 | 2388 | 2389 | 2390 | 2391 | 2392 | 2393 | 2394 | 2395 | 2396 | 2397 | 2398 | 2399 | 2400 | 2401 | 2402 | 2403 | 2404 | 2405 | 2406 | 2407 | 2408 | 2409 | 2410 | 2411 | 2412 | 2413 | 2414 | 2415 | 2416 | 2417 | 2418 | 2419 | 2420 | 2421 | 2422 | 2423 | 2424 | 2425 | 2426 | 2427 | 2428 | 2429 | 2430 | 2431 | 2432 | 2433 | 2434 | 2435 | 2436 | 2437 | 2438 | 2439 | 2440 | 2441 | 2442 | 2443 | 2444 | 2445 | 2446 | 2447 | 2448 | 2449 | 2450 | 2451 | 2452 | 2453 | 2454 | 2455 | 2456 | 2457 | 2458 | 2459 | 2460 | 2461 | 2462 | 2463 | 2464 | 2465 | 2466 | 2467 | 2468 | 2469 | 2470 | 2471 | 2472 | 2473 | 2474 | 2475 | 2476 | 2477 | 2478 | 2479 | 2480 | 2481 | 2482 | 2483 | 2484 | 2485 | 2486 | 2487 | 2488 | 2489 | 2490 | 2491 | 2492 | 2493 | 2494 | 2495 | 2496 | 2497 | 2498 | 2499 | 2500 | 2501 | 2502 | 2503 | 2504 | 2505 | 2506 | 2507 | 2508 | 2509 | 2510 | 2511 | 2512 | 2513 | 2514 | 2515 | 2516 | 2517 | 2518 | 2519 | 2520 | 2521 | 2522 | 2523 | 2524 | 2525 | 2526 | 2527 | 2528 | 2529 | 2530 | 2531 | 2532 | 2533 | 2534 | 2535 | 2536 | 2537 | 2538 | 2539 | 2540 | 2541 | 2542 | 2543 | 2544 | 2545 | 2546 | 2547 | 2548 | 2549 | 2550 | 2551 | 2552 | 2553 | 2554 | 2555 | 2556 | 2557 | 2558 | 2559 | 2560 | 2561 | 2562 | 2563 | 2564 | 2565 | 2566 | 2567 | 2568 | 2569 | 2570 | 2571 | 2572 | 2573 | 2574 | 2575 | 2576 | 2577 | 2578 | 2579 | 2580 | 2581 | 2582 | 2583 | 2584 | 2585 | 2586 | 2587 | 2588 | 2589 | 2590 | 2591 | 2592 | 2593 | 2594 | 2595 | 2596 | 2597 | 2598 | 2599 | 2600 | 2601 | 2602 | 2603 | 2604 | 2605 | 2606 | 2607 | 2608 | 2609 | 2610 | 2611 | 2612 | 2613 | 2614 | 2615 | 2616 | 2617 | 2618 | 2619 | 2620 | 2621 | 2622 | 2623 | 2624 | 2625 | 2626 | 2627 | 2628 | 2629 | 2630 | 2631 | 2632 | 2633 | 2634 | 2635 | 2636 | 2637 | 2638 | 2639 | 2640 | 2641 | 2642 | 2643 | 2644 | 2645 | 2646 | 2647 | 2648 | 2649 | 2650 | 2651 | 2652 | 2653 | 2654 | 2655 | 2656 | 2657 | 2658 | 2659 | 2660 | 2661 | 2662 | 2663 | 2664 | 2665 | 2666 | 2667 | 2668 | 2669 | 2670 | 2671 | 2672 | 2673 | 2674 | 2675 | 2676 | 2677 | 2678 | 2679 | 2680 | 2681 | 2682 | 2683 | 2684 | 2685 | 2686 | 2687 | 2688 | 2689 | 2690 | 2691 | 2692 | 2693 | 2694 | 2695 | 2696 | 2697 | 2698 | 2699 | 2700 | 2701 | 2702 | 2703 | 2704 | 2705 | 2706 | 2707 | 2708 | 2709 | 2710 | 2711 | 2712 | 2713 | 2714 | 2715 | 2716 | 2717 | 2718 | 2719 | 2720 | 2721 | 2722 | 2723 | 2724 | 2725 | 2726 | 2727 | 2728 | 2729 | 2730 | 2731 | 2732 | 2733 | 2734 | 2735 | 2736 | 2737 | 2738 | 2739 | 2740 | 2741 | 2742 | 2743 | 2744 | 2745 | 2746 | 2747 | 2748 | 2749 | 2750 | 2751 | 2752 | 2753 | 2754 | 2755 | 2756 | 2757 | 2758 | 2759 | 2760 | 2761 | 2762 | 2763 | 2764 | 2765 | 2766 | 2767 | 2768 | 2769 | 2770 | 2771 | 2772 | 2773 | 2774 | 2775 | 2776 | 2777 | 2778 | 2779 | 2780 | 2781 | 2782 | 2783 | 2784 | 2785 | 2786 | 2787 | 2788 | 2789 | 2790 | 2791 | 2792 | 2793 | 2794 | 2795 | 2796 | 2797 | 2798 | 2799 | 2800 | 2801 | 2802 | 2803 | 2804 | 2805 | 2806 | 2807 | 2808 | 2809 | 2810 | 2811 | 2812 | 2813 | 2814 | 2815 | 2816 | 2817 | 2818 | 2819 | 2820 | 2821 | 2822 | 2823 | 2824 | 2825 | 2826 | 2827 | 2828 | 2829 | 2830 | 2831 | 2832 | 2833 | 2834 | 2835 | 2836 | 2837 | 2838 | 2839 | 2840 | 2841 | 2842 | 2843 | 2844 | 2845 | 2846 | 2847 | 2848 | 2849 | 2850 | 2851 | 2852 | 2853 | 2854 | 2855 | 2856 | 2857 | 2858 | 2859 | 2860 | 2861 | 2862 | 2863 | 2864 | 2865 | 2866 | 2867 | 2868 | 2869 | 2870 | 2871 | 2872 | 2873 | 2874 | 2875 | 2876 | 2877 | 2878 | 2879 | 2880 | 2881 | 2882 | 2883 | 2884 | 2885 | 2886 | 2887 | 2888 | 2889 | 2890 | 2891 | 2892 | 2893 | 2894 | 2895 | 2896 | 2897 | 2898 | 2899 | 2900 | 2901 | 2902 | 2903 | 2904 | 2905 | 2906 | 2907 | 2908 | 2909 | 2910 | 2911 | 2912 | 2913 | 2914 | 2915 | 2916 | 2917 | 2918 | 2919 | 2920 | 2921 | 2922 | 2923 | 2924 | 2925 | 2926 | 2927 | 2928 | 2929 | 2930 | 2931 | 2932 | 2933 | 2934 | 2935 | 2936 | 2937 | 2938 | 2939 | 2940 | 2941 | 2942 | 2943 | 2944 | 2945 | 2946 | 2947 | 2948 | 2949 | 2950 | 2951 | 2952 | 2953 | 2954 | 2955 | 2956 | 2957 | 2958 | 2959 | 2960 | 2961 | 2962 | 2963 | 2964 | 2965 | 2966 | 2967 | 2968 | 2969 | 2970 | 2971 | 2972 | 2973 | 2974 | 2975 | 2976 | 2977 | 2978 | 2979 | 2980 | 2981 | 2982 | 2983 | 2984 | 2985 | 2986 | 2987 | 2988 | 2989 | 2990 | 2991 | 2992 | 2993 | 2994 | 2995 | 2996 | 2997 | 2998 | 2999 | 3000 | 3001 | 3002 | 3003 | 3004 | 3005 | 3006 | 3007 | 3008 | 3009 | 3010 | 3011 | 3012 | 3013 | 3014 | 3015 | 3016 | 3017 | 3018 | 3019 | 3020 | 3021 | 3022 | 3023 | 3024 | 3025 | 3026 | 3027 | 3028 | 3029 | 3030 | 3031 | 3032 | 3033 | 3034 | 3035 | 3036 | 3037 | 3038 | 3039 | 3040 | 3041 | 3042 | 3043 | 3044 | 3045 | 3046 | 3047 | 3048 | 3049 | 3050 | 3051 | 3052 | 3053 | 3054 | 3055 | 3056 | 3057 | 3058 | 3059 | 3060 | 3061 | 3062 | 3063 | 3064 | 3065 | 3066 | 3067 | 3068 | 3069 | 3070 | 3071 | 3072 | 3073 | 3074 | 3075 | 3076 | 3077 | 3078 | 3079 | 3080 | 3081 | 3082 | 3083 | 3084 | 3085 | 3086 | 3087 | 3088 | 3089 | 3090 | 3091 | 3092 | 3093 | 3094 | 3095 | 3096 | 3097 | 3098 | 3099 | 3100 | 3101 | 3102 | 3103 | 3104 | 3105 | 3106 | 3107 | 3108 | 3109 | 3110 | 3111 | 3112 | 3113 | 3114 | 3115 | 3116 | 3117 | 3118 | 3119 | 3120 | 3121 | 3122 | 3123 | 3124 | 3125 | 3126 | 3127 | 3128 | 3129 | 3130 | 3131 | 3132 | 3133 | 3134 | 3135 | 3136 | 3137 | 3138 | 3139 | 3140 | 3141 | 3142 | 3143 | 3144 | 3145 | 3146 | 3147 | 3148 | 3149 | 3150 | 3151 | 3152 | 3153 | 3154 | 3155 | 3156 | 3157 | 3158 | 3159 | 3160 | 3161 | 3162 | 3163 | 3164 | 3165 | 3166 | 3167 | 3168 | 3169 | 3170 | 3171 | 3172 | 3173 | 3174 | 3175 | 3176 | 3177 | 3178 | 3179 | 3180 | 3181 | 3182 | 3183 | 3184 | 3185 | 3186 | 3187 | 3188 | 3189 | 3190 | 3191 | 3192 | 3193 | 3194 | 3195 | 3196 | 3197 | 3198 | 3199 | 3200 | 3201 | 3202 | 3203 | 3204 | 3205 | 3206 | 3207 | 3208 | 3209 | 3210 | 3211 | 3212 | 3213 | 3214 | 3215 | 3216 | 3217 | 3218 | 3219 | 3220 | 3221 | 3222 | 3223 | 3224 | 3225 | 3226 | 3227 | 3228 | 3229 | 3230 | 3231 | 3232 | 3233 | 3234 | 3235 | 3236 | 3237 | 3238 | 3239 | 3240 | 3241 | 3242 | 3243 | 3244 | 3245 | 3246 | 3247 | 3248 | 3249 | 3250 | 3251 | 3252 | 3253 | 3254 | 3255 | 3256 | 3257 | 3258 | 3259 | 3260 | 3261 | 3262 | 3263 | 3264 | 3265 | 3266 | 3267 | 3268 | 3269 | 3270 | 3271 | 3272 | 3273 | 3274 | 3275 | 3276 | 3277 | 3278 | 3279 | 3280 | 3281 | 3282 | 3283 | 3284 | 3285 | 3286 | 3287 | 3288 | 3289 | 3290 | 3291 | 3292 | 3293 | 3294 | 3295 | 3296 | 3297 | 3298 | 3299 | 3300 | 3301 | 3302 | 3303 | 3304 | 3305 | 3306 | 3307 | 3308 | 3309 | 3310 | 3311 | 3312 | 3313 | 3314 | 3315 | 3316 | 3317 | 3318 | 3319 | 3320 | 3321 | 3322 | 3323 | 3324 | 3325 | 3326 | 3327 | 3328 | 3329 | 3330 | 3331 | 3332 | 3333 | 3334 | 3335 | 3336 | 3337 | 3338 | 3339 | 3340 | 3341 | 3342 | 3343 | 3344 | 3345 | 3346 | 3347 | 3348 | 3349 | 3350 | 3351 | 3352 | 3353 | 3354 | 3355 | 3356 | 3357 | 3358 | 3359 | 3360 | 3361 | 3362 | 3363 | 3364 | 3365 | 3366 | 3367 | 3368 | 3369 | 3370 | 3371 | 3372 | 3373 | 3374 | 3375 | 3376 | 3377 | 3378 | 3379 | 3380 | 3381 | 3382 | 3383 | 3384 | 3385 | 3386 | 3387 | 3388 | 3389 | 3390 | 3391 | 3392 | 3393 | 3394 | 3395 | 3396 | 3397 | 3398 | 3399 | 3400 | 3401 | 3402 | 3403 | 3404 | 3405 | 3406 | 3407 | 3408 | 3409 | 3410 | 3411 | 3412 | 3413 | 3414 | 3415 | 3416 | 3417 | 3418 | 3419 | 3420 | 3421 | 3422 | 3423 | 3424 | 3425 | 3426 | 3427 | 3428 | 3429 | 3430 | 3431 | 3432 | 3433 | 3434 | 3435 | 3436 | 3437 | 3438 | 3439 | 3440 | 3441 | 3442 | 3443 | 3444 | 3445 | 3446 | 3447 | 3448 | 3449 | 3450 | 3451 | 3452 | 3453 | 3454 | 3455 | 3456 | 3457 | 3458 | 3459 | 3460 | 3461 | 3462 | 3463 | 3464 | 3465 | 3466 | 3467 | 3468 | 3469 | 3470 | 3471 | 3472 | 3473 | 3474 | 3475 | 3476 | 3477 | 3478 | 3479 | 3480 | 3481 | 3482 | 3483 | 3484 | 3485 | 3486 | 3487 | 3488 | 3489 | 3490 | 3491 | 3492 | 3493 | 3494 | 3495 | 3496 | 3497 | 3498 | 3499 | 3500 | 3501 | 3502 | 3503 | 3504 | 3505 | 3506 | 3507 | 3508 | 3509 | 3510 | 3511 | 3512 | 3513 | 3514 | 3515 | 3516 | 3517 | 3518 | 3519 | 3520 | 3521 | 3522 | 3523 | 3524 | 3525 | 3526 | 3527 | 3528 | 3529 | 3530 | 3531 | 3532 | 3533 | 3534 | 3535 | 3536 | 3537 | 3538 | 3539 | 3540 | 3541 | 3542 | 3543 | 3544 | 3545 | 3546 | 3547 | 3548 | 3549 | 3550 | 3551 | 3552 | 3553 | 3554 | 3555 | 3556 | 3557 | 3558 | 3559 | 3560 | 3561 | 3562 | 3563 | 3564 | 3565 | 3566 | 3567 | 3568 | 3569 | 3570 | 3571 | 3572 | 3573 | 3574 | 3575 | 3576 | 3577 | 3578 | 3579 | 3580 | 3581 | 3582 | 3583 | 3584 | 3585 | 3586 | 3587 | 3588 | 3589 | 3590 | 3591 | 3592 | 3593 | 3594 | 3595 | 3596 | 3597 | 3598 | 3599 | 3600 | 3601 | 3602 | 3603 | 3604 | 3605 | 3606 | 3607 | 3608 | 3609 | 3610 | 3611 | 3612 | 3613 | 3614 | 3615 | 3616 | 3617 | 3618 | 3619 | 3620 | 3621 | 3622 | 3623 | 3624 | 3625 | 3626 | 3627 | 3628 | 3629 | 3630 | 3631 | 3632 | 3633 | 3634 | 3635 | 3636 | 3637 | 3638 | 3639 | 3640 | 3641 | 3642 | 3643 | 3644 | 3645 | 3646 | 3647 | 3648 | 3649 | 3650 | 3651 | 3652 | 3653 | 3654 | 3655 | 3656 | 3657 | 3658 | 3659 | 3660 | 3661 | 3662 | 3663 | 3664 | 3665 | 3666 | 3667 | 3668 | 3669 | 3670 | 3671 | 3672 | 3673 | 3674 | 3675 | 3676 | 3677 | 3678 | 3679 | 3680 | 3681 | 3682 | 3683 | 3684 | 3685 | 3686 | 3687 | 3688 | 3689 | 3690 | 3691 | 3692 | 3693 | 3694 | 3695 | 3696 | 3697 | 3698 | 3699 | 3700 | 3701 | 3702 | 3703 | 3704 | 3705 | 3706 | 3707 | 3708 | 3709 | 3710 | 3711 | 3712 | 3713 | 3714 | 3715 | 3716 | 3717 | 3718 | 3719 | 3720 | 3721 | 3722 | 3723 | 3724 | 3725 | 3726 | 3727 | 3728 | 3729 | 3730 | 3731 | 3732 | 3733 | 3734 | 3735 | 3736 | 3737 | 3738 | 3739 | 3740 | 3741 | 3742 | 3743 | 3744 | 3745 | 3746 | 3747 | 3748 | 3749 | 3750 | 3751 | 3752 | 3753 | 3754 | 3755 | 3756 | 3757 | 3758 | 3759 | 3760 | 3761 | 3762 | 3763 | 3764 | 3765 | 3766 | 3767 | 3768 | 3769 | 3770 | 3771 | 3772 | 3773 | 3774 | 3775 | 3776 | 3777 | 3778 | 3779 | 3780 | 3781 | 3782 | 3783 | 3784 | 3785 | 3786 | 3787 | 3788 | 3789 | 3790 | 3791 | 3792 | 3793 | 3794 | 3795 | 3796 | 3797 | 3798 | 3799 | 3800 | 3801 | 3802 | 3803 | 3804 | 3805 | 3806 | 3807 | 3808 | 3809 | 3810 | 3811 | 3812 | 3813 | 3814 | 3815 | 3816 | 3817 | 3818 | 3819 | 3820 | 3821 | 3822 | 3823 | 3824 | 3825 | 3826 | 3827 | 3828 | 3829 | 3830 | 3831 | 3832 | 3833 | 3834 | 3835 | 3836 | 3837 | 3838 | 3839 | 3840 | 3841 | 3842 | 3843 | 3844 | 3845 | 3846 | 3847 | 3848 | 3849 | 3850 | 3851 | 3852 | 3853 | 3854 | 3855 | 3856 | 3857 | 3858 | 3859 | 3860 | 3861 | 3862 | 3863 | 3864 | 3865 | 3866 | 3867 | 3868 | 3869 | 3870 | 3871 | 3872 | 3873 | 3874 | 3875 | 3876 | 3877 | 3878 | 3879 | 3880 | 3881 | 3882 | 3883 | 3884 | 3885 | 3886 | 3887 | 3888 | 3889 | 3890 | 3891 | 3892 | 3893 | 3894 | 3895 | 3896 | 3897 | 3898 | 3899 | 3900 | 3901 | 3902 | 3903 | 3904 | 3905 | 3906 | 3907 | 3908 | 3909 | 3910 | 3911 | 3912 | 3913 | 3914 | 3915 | 3916 | 3917 | 3918 | 3919 | 3920 | 3921 | 3922 | 3923 | 3924 | 3925 | 3926 | 3927 | 3928 | 3929 | 3930 | 3931 | 3932 | 3933 | 3934 | 3935 | 3936 | 3937 | 3938 | 3939 | 3940 | 3941 | 3942 | 3943 | 3944 | 3945 | 3946 | 3947 | 3948 | 3949 | 3950 | 3951 | 3952 | 3953 | 3954 | 3955 | 3956 | 3957 | 3958 | 3959 | 3960 | 3961 | 3962 | 3963 | 3964 | 3965 | 3966 | 3967 | 3968 | 3969 | 3970 | 3971 | 3972 | 3973 | 3974 | 3975 | 3976 | 3977 | 3978 | 3979 | 3980 | 3981 | 3982 | 3983 | 3984 | 3985 | 3986 | 3987 | 3988 | 3989 | 3990 | 3991 | 3992 | 3993 | 3994 | 3995 | 3996 | 3997 | 3998 | 3999 | 4000 | 4001 | 4002 | 4003 | 4004 | 4005 | 4006 | 4007 | 4008 | 4009 | 4010 | 4011 | 4012 | 4013 | 4014 | 4015 | 4016 | 4017 | 4018 | 4019 | 4020 | 4021 | 4022 | 4023 | 4024 | 4025 | 4026 | 4027 | 4028 | 4029 | 4030 | 4031 | 4032 | 4033 | 4034 | 4035 | 4036 | 4037 | 4038 | 4039 | 4040 | 4041 | 4042 | 4043 | 4044 | 4045 | 4046 | 4047 | 4048 | 4049 | 4050 | 4051 | 4052 | 4053 | 4054 | 4055 | 4056 | 4057 | 4058 | 4059 | 4060 | 4061 | 4062 | 4063 | 4064 | 4065 | 4066 | 4067 | 4068 | 4069 | 4070 | 4071 | 4072 | 4073 | 4074 | 4075 | 4076 | 4077 | 4078 | 4079 | 4080 | 4081 | 4082 | 4083 | 4084 | 4085 | 4086 | 4087 | 4088 | 4089 | 4090 | 4091 | 4092 | 4093 | 4094 | 4095 | 4096 | 4097 | 4098 | 4099 | 4100 | 4101 | 4102 | 4103 | 4104 | 4105 | 4106 | 4107 | 4108 | 4109 | 4110 | 4111 | 4112 | 4113 | 4114 | 4115 | 4116 | 4117 | 4118 | 4119 | 4120 | 4121 | 4122 | 4123 | 4124 | 4125 | 4126 | 4127 | 4128 | 4129 | 4130 | 4131 | 4132 | 4133 | 4134 | 4135 | 4136 | 4137 | 4138 | 4139 | 4140 | 4141 | 4142 | 4143 | 4144 | 4145 | 4146 | 4147 | 4148 | 4149 | 4150 | 4151 | 4152 | 4153 | 4154 | 4155 | 4156 | 4157 | 4158 | 4159 | 4160 | 4161 | 4162 | 4163 | 4164 | 4165 | 4166 | 4167 | 4168 | 4169 | 4170 | 4171 | 4172 | 4173 | 4174 | 4175 | 4176 | 4177 | 4178 | 4179 | 4180 | 4181 | 4182 | 4183 | 4184 | 4185 | 4186 | 4187 | 4188 | 4189 | 4190 | 4191 | 4192 | 4193 | 4194 | 4195 | 4196 | 4197 | 4198 | 4199 | 4200 | 4201 | 4202 | 4203 | 4204 | 4205 | 4206 | 4207 | 4208 | 4209 | 4210 | 4211 | 4212 | 4213 | 4214 | 4215 | 4216 | 4217 | 4218 | 4219 | 4220 | 4221 | 4222 | 4223 | 4224 | 4225 | 4226 | 4227 | 4228 | 4229 | 4230 | 4231 | 4232 | 4233 | 4234 | 4235 | 4236 | 4237 | 4238 | 4239 | 4240 | 4241 | 4242 | 4243 | 4244 | 4245 | 4246 | 4247 | 4248 | 4249 | 4250 | 4251 | 4252 | 4253 | 4254 | 4255 | 4256 | 4257 | 4258 | 4259 | 4260 | 4261 | 4262 | 4263 | 4264 | 4265 | 4266 | 4267 | 4268 | 4269 | 4270 | 4271 | 4272 | 4273 | 4274 | 4275 | 4276 | 4277 | 4278 | 4279 | 4280 | 4281 | 4282 | 4283 | 4284 | 4285 | 4286 | 4287 | 4288 | 4289 | 4290 | 4291 | 4292 | 4293 | 4294 | 4295 | 4296 | 4297 | 4298 | 4299 | 4300 | 4301 | 4302 | 4303 | 4304 | 4305 | 4306 | 4307 | 4308 | 4309 | 4310 | 4311 | 4312 | 4313 | 4314 | 4315 | 4316 | 4317 | 4318 | 4319 | 4320 | 4321 | 4322 | 4323 | 4324 | 4325 | 4326 | 4327 | 4328 | 4329 | 4330 | 4331 | 4332 | 4333 | 4334 | 4335 | 4336 | 4337 | 4338 | 4339 | 4340 | 4341 | 4342 | 4343 | 4344 | 4345 | 4346 | 4347 | 4348 | 4349 | 4350 | 4351 | 4352 | 4353 | 4354 | 4355 | 4356 | 4357 | 4358 | 4359 | 4360 | 4361 | 4362 | 4363 | 4364 | 4365 | 4366 | 4367 | 4368 | 4369 | 4370 | 4371 | 4372 | 4373 | 4374 | 4375 | 4376 | 4377 | 4378 | 4379 | 4380 | 4381 | 4382 | 4383 | 4384 | 4385 | 4386 | 4387 | 4388 | 4389 | 4390 | 4391 | 4392 | 4393 | 4394 | 4395 | 4396 | 4397 | 4398 | 4399 | 4400 | 4401 | 4402 | 4403 | 4404 | 4405 | 4406 | 4407 | 4408 | 4409 | 4410 | 4411 | 4412 | 4413 | 4414 | 4415 | 4416 | 4417 | 4418 | 4419 | 4420 | 4421 | 4422 | 4423 | 4424 | 4425 | 4426 | 4427 | 4428 | 4429 | 4430 | 4431 | 4432 | 4433 | 4434 | 4435 | 4436 | 4437 | 4438 | 4439 | 4440 | 4441 | 4442 | 4443 | 4444 | 4445 | 4446 | 4447 | 4448 | 4449 | 4450 | 4451 | 4452 | 4453 | 4454 | 4455 | 4456 | 4457 | 4458 | 4459 | 4460 | 4461 | 4462 | 4463 | 4464 | 4465 | 4466 | 4467 | 4468 | 4469 | 4470 | 4471 | 4472 | 4473 | 4474 | 4475 | 4476 | 4477 | 4478 | 4479 | 4480 | 4481 | 4482 | 4483 | 4484 | 4485 | 4486 | 4487 | 4488 | 4489 | 4490 | 4491 | 4492 | 4493 | 4494 | 4495 | 4496 | 4497 | 4498 | 4499 | 4500 | 4501 | 4502 | 4503 | 4504 | 4505 | 4506 | 4507 | 4508 | 4509 | 4510 | 4511 | 4512 | 4513 | 4514 | 4515 | 4516 | 4517 | 4518 | 4519 | 4520 | 4521 | 4522 | 4523 | 4524 | 4525 | 4526 | 4527 | 4528 | 4529 | 4530 | 4531 | 4532 | 4533 | 4534 | 4535 | 4536 | 4537 | 4538 | 4539 | 4540 | 4541 | 4542 | 4543 | 4544 | 4545 | 4546 | 4547 | 4548 | 4549 | 4550 | 4551 | 4552 | 4553 | 4554 | 4555 | 4556 | 4557 | 4558 | 4559 | 4560 | 4561 | 4562 | 4563 | 4564 | 4565 | 4566 | 4567 | 4568 | 4569 | 4570 | 4571 | 4572 | 4573 | 4574 | 4575 | 4576 | 4577 | 4578 | 4579 | 4580 | 4581 | 4582 | 4583 | 4584 | 4585 | 4586 | 4587 | 4588 | 4589 | 4590 | 4591 | 4592 | 4593 | 4594 | 4595 | 4596 | 4597 | 4598 | 4599 | 4600 | 4601 | 4602 | 4603 | 4604 | 4605 | 4606 | 4607 | 4608 | 4609 | 4610 | 4611 | 4612 | 4613 | 4614 | 4615 | 4616 | 4617 | 4618 | 4619 | 4620 | 4621 | 4622 | 4623 | 4624 | 4625 | 4626 | 4627 | 4628 | 4629 | 4630 | 4631 | 4632 | 4633 | 4634 | 4635 | 4636 | 4637 | 4638 | 4639 | 4640 | 4641 | 4642 | 4643 | 4644 | 4645 | 4646 | 4647 | 4648 | 4649 | 4650 | 4651 | 4652 | 4653 | 4654 | 4655 | 4656 | 4657 | 4658 | 4659 | 4660 | 4661 | 4662 | 4663 | 4664 | 4665 | 4666 | 4667 | 4668 | 4669 | 4670 | 4671 | 4672 | 4673 | 4674 | 4675 | 4676 | 4677 | 4678 | 4679 | 4680 | 4681 | 4682 | 4683 | 4684 | 4685 | 4686 | 4687 | 4688 | 4689 | 4690 | 4691 | 4692 | 4693 | 4694 | 4695 | 4696 | 4697 | 4698 | 4699 | 4700 | 4701 | 4702 | 4703 | 4704 | 4705 | 4706 | 4707 | 4708 | 4709 | 4710 | 4711 | 4712 | 4713 | 4714 | 4715 | 4716 | 4717 | 4718 | 4719 | 4720 | 4721 | 4722 | 4723 | 4724 | 4725 | 4726 | 4727 | 4728 | 4729 | 4730 | 4731 | 4732 | 4733 | 4734 | 4735 | 4736 | 4737 | 4738 | 4739 | 4740 | 4741 | 4742 | 4743 | 4744 | 4745 | 4746 | 4747 | 4748 | 4749 | 4750 | 4751 | 4752 | 4753 | 4754 | 4755 | 4756 | 4757 | 4758 | 4759 | 4760 | 4761 | 4762 | 4763 | 4764 | 4765 | 4766 | 4767 | 4768 | 4769 | 4770 | 4771 | 4772 | 4773 | 4774 | 4775 | 4776 | 4777 | 4778 | 4779 | 4780 | 4781 | 4782 | 4783 | 4784 | 4785 | 4786 | 4787 | 4788 | 4789 | 4790 | 4791 | 4792 | 4793 | 4794 | 4795 | 4796 | 4797 | 4798 | 4799 | 4800 | 4801 | 4802 | 4803 | 4804 | 4805 | 4806 | 4807 | 4808 | 4809 | 4810 | 4811 | 4812 | 4813 | 4814 | 4815 | 4816 | 4817 | 4818 | 4819 | 4820 | 4821 | 4822 | 4823 | 4824 | 4825 | 4826 | 4827 | 4828 | 4829 | 4830 | 4831 | 4832 | 4833 | 4834 | 4835 | 4836 | 4837 | 4838 | 4839 | 4840 | 4841 | 4842 | 4843 | 4844 | 4845 | 4846 | 4847 | 4848 | 4849 | 4850 | 4851 | 4852 | 4853 | 4854 | 4855 | 4856 | 4857 | 4858 | 4859 | 4860 | 4861 | 4862 | 4863 | 4864 | 4865 | 4866 | 4867 | 4868 | 4869 | 4870 | 4871 | 4872 | 4873 | 4874 | 4875 | 4876 | 4877 | 4878 | 4879 | 4880 | 4881 | 4882 | 4883 | 4884 | 4885 | 4886 | 4887 | 4888 | 4889 | 4890 | 4891 | 4892 | 4893 | 4894 | 4895 | 4896 | 4897 | 4898 | 4899 | 4900 | 4901 | 4902 | 4903 | 4904 | 4905 | 4906 | 4907 | 4908 | 4909 | 4910 | 4911 | 4912 | 4913 | 4914 | 4915 | 4916 | 4917 | 4918 | 4919 | 4920 | 4921 | 4922 | 4923 | 4924 | 4925 | 4926 | 4927 | 4928 | 4929 | 4930 | 4931 | 4932 | 4933 | 4934 | 4935 | 4936 | 4937 | 4938 | 4939 | 4940 | 4941 | 4942 | 4943 | 4944 | 4945 | 4946 | 4947 | 4948 | 4949 | 4950 | 4951 | 4952 | 4953 | 4954 | 4955 | 4956 | 4957 | 4958 | 4959 | 4960 | 4961 | 4962 | 4963 | 4964 | 4965 | 4966 | 4967 | 4968 | 4969 | 4970 | 4971 | 4972 | 4973 | 4974 | 4975 | 4976 | 4977 | 4978 | 4979 | 4980 | 4981 | 4982 | 4983 | 4984 | 4985 | 4986 | 4987 | 4988 | 4989 | 4990 | 4991 | 4992 | 4993 | 4994 | 4995 | 4996 | 4997 | 4998 | 4999 | 5000 | 5001 | 5002 | 5003 | 5004 | 5005 | 5006 | 5007 | 5008 | 5009 | 5010 | 5011 | 5012 | 5013 | 5014 | 5015 | 5016 | 5017 | 5018 | 5019 | 5020 | 5021 | 5022 | 5023 | 5024 | 5025 | 5026 | 5027 | 5028 | 5029 | 5030 | 5031 | 5032 | 5033 | 5034 | 5035 | 5036 | 5037 | 5038 | 5039 | 5040 | 5041 | 5042 | 5043 | 5044 | 5045 | 5046 | 5047 | 5048 | 5049 | 5050 | 5051 | 5052 | 5053 | 5054 | 5055 | 5056 | 5057 | 5058 | 5059 | 5060 | 5061 | 5062 | 5063 | 5064 | 5065 | 5066 | 5067 | 5068 | 5069 | 5070 | 5071 | 5072 | 5073 | 5074 | 5075 | 5076 | 5077 | 5078 | 5079 | 5080 | 5081 | 5082 | 5083 | 5084 | 5085 | 5086 | 5087 | 5088 | 5089 | 5090 | 5091 | 5092 | 5093 | 5094 | 5095 | 5096 | 5097 | 5098 | 5099 | 5100 | 5101 | 5102 | 5103 | 5104 | 5105 | 5106 | 5107 | 5108 | 5109 | 5110 | 5111 | 5112 | 5113 | 5114 | 5115 | 5116 | 5117 | 5118 | 5119 | 5120 | 5121 | 5122 | 5123 | 5124 | 5125 | 5126 | 5127 | 5128 | 5129 | 5130 | 5131 | 5132 | 5133 | 5134 | 5135 | 5136 | 5137 | 5138 | 5139 | 5140 | 5141 | 5142 | 5143 | 5144 | 5145 | 5146 | 5147 | 5148 | 5149 | 5150 | 5151 | 5152 | 5153 | 5154 | 5155 | 5156 | 5157 | 5158 | 5159 | 5160 | 5161 | 5162 | 5163 | 5164 | 5165 | 5166 | 5167 | 5168 | 5169 | 5170 | 5171 | 5172 | 5173 | 5174 | 5175 | 5176 | 5177 | 5178 | 5179 | 5180 | 5181 | 5182 | 5183 | 5184 | 5185 | 5186 | 5187 | 5188 | 5189 | 5190 | 5191 | 5192 | 5193 | 5194 | 5195 | 5196 | 5197 | 5198 | 5199 | 5200 | 5201 | 5202 | 5203 | 5204 | 5205 | 5206 | 5207 | 5208 | 5209 | 5210 | 5211 | 5212 | 5213 | 5214 | 5215 | 5216 | 5217 | 5218 | 5219 | 5220 | 5221 | 5222 | 5223 | 5224 | 5225 | 5226 | 5227 | 5228 | 5229 | 5230 | 5231 | 5232 | 5233 | 5234 | 5235 | 5236 | 5237 | 5238 | 5239 | 5240 | 5241 | 5242 | 5243 | 5244 | 5245 | 5246 | 5247 | 5248 | 5249 | 5250 | 5251 | 5252 | 5253 | 5254 | 5255 | 5256 | 5257 | 5258 | 5259 | 5260 | 5261 | 5262 | 5263 | 5264 | 5265 | 5266 | 5267 | 5268 | 5269 | 5270 | 5271 | 5272 | 5273 | 5274 | 5275 | 5276 | 5277 | 5278 | 5279 | 5280 | 5281 | 5282 | 5283 | 5284 | 5285 | 5286 | 5287 | 5288 | 5289 | 5290 | 5291 | 5292 | 5293 | 5294 | 5295 | 5296 | 5297 | 5298 | 5299 | 5300 | 5301 | 5302 | 5303 | 5304 | 5305 | 5306 | 5307 | 5308 | 5309 | 5310 | 5311 | 5312 | 5313 | 5314 | 5315 | 5316 | 5317 | 5318 | 5319 | 5320 | 5321 | 5322 | 5323 | 5324 | 5325 | 5326 | 5327 | 5328 | 5329 | 5330 | 5331 | 5332 | 5333 | 5334 | 5335 | 5336 | 5337 | 5338 | 5339 | 5340 | 5341 | 5342 | 5343 | 5344 | 5345 | 5346 | 5347 | 5348 | 5349 | 5350 | 5351 | 5352 | 5353 | 5354 | 5355 | 5356 | 5357 | 5358 | 5359 | 5360 | 5361 | 5362 | 5363 | 5364 | 5365 | 5366 | 5367 | 5368 | 5369 | 5370 | 5371 | 5372 | 5373 | 5374 | 5375 | 5376 | 5377 | 5378 | 5379 | 5380 | 5381 | 5382 | 5383 | 5384 | 5385 | 5386 | 5387 | 5388 | 5389 | 5390 | 5391 | 5392 | 5393 | 5394 | 5395 | 5396 | 5397 | 5398 | 5399 | 5400 | 5401 | 5402 | 5403 | 5404 | 5405 | 5406 | 5407 | 5408 | 5409 | 5410 | 5411 | 5412 | 5413 | 5414 | 5415 | 5416 | 5417 | 5418 | 5419 | 5420 | 5421 | 5422 | 5423 | 5424 | 5425 | 5426 | 5427 | 5428 | 5429 | 5430 | 5431 | 5432 | 5433 | 5434 | 5435 | 5436 | 5437 | 5438 | 5439 | 5440 | 5441 | 5442 | 5443 | 5444 | 5445 | 5446 | 5447 | 5448 | 5449 | 5450 | 5451 | 5452 | 5453 | 5454 | 5455 | 5456 | 5457 | 5458 | 5459 | 5460 | 5461 | 5462 | 5463 | 5464 | 5465 | 5466 | 5467 | 5468 | 5469 | 5470 | 5471 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Max_201307 | 0.0680335 | 0.0877499 | 0.1829367 | -0.0479014 | 0.0364684 | -0.0147671 | 0.0664152 | -0.0511395 | 0.0594114 | -0.0452959 | -0.0511395 | -0.0511395 | 0.0287402 | -0.0511395 | 0.1943523 | -0.0511395 | 0.0225546 | -0.0511395 | -0.0511395 | 0.1564551 | -0.0511395 | 0.0463846 | -0.0511395 | 0.1040651 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0021854 | -0.0511395 | 0.0629322 | 0.8628800 | -0.0511395 | 0.0037863 | 0.1231788 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1013238 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0399046 | -0.0249905 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1805498 | -0.0511395 | -0.0511395 | 0.2955259 | -0.0511395 | -0.0511395 | 0.0117287 | -0.0511395 | 0.0272403 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3518067 | 0.0583140 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0487943 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0399352 | -0.0166259 | -0.0511395 | -0.0511395 | -0.0062752 | -0.0511395 | -0.0511395 | 0.1292405 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0310169 | 0.0842571 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0473380 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0997500 | -0.0511395 | 0.0653454 | -0.0511395 | -0.0511395 | 0.1073868 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0649810 | -0.0511395 | -0.0511395 | 0.0088948 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0753807 | -0.0511395 | -0.0304486 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0288533 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0577260 | -0.0511395 | -0.0511395 | 0.2649228 | -0.0511395 | -0.0511395 | 0.0380628 | -0.0511395 | -0.0511395 | 0.0198789 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1602340 | 0.0766639 | -0.0318570 | -0.0511395 | -0.0457635 | 0.1368587 | -0.0511395 | -0.0511395 | 0.0927318 | 0.0471384 | 0.0664082 | -0.0309399 | 0.0075686 | -0.0353743 | 0.0453435 | -0.0049359 | 0.0712726 | -0.0340825 | -0.0006144 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0907564 | 0.0261185 | -0.0511395 | 0.2625260 | -0.0472115 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0115353 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0944237 | 0.0621262 | -0.0511395 | -0.0511395 | 0.0828648 | 0.0536908 | -0.0511395 | 0.1242027 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1035297 | -0.0511395 | 0.1117904 | -0.0511395 | -0.0352859 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0649303 | 0.0177769 | 0.0619771 | 0.0229054 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0490809 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2433921 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0688337 | -0.0511395 | -0.0511395 | 73.2674177 | -0.0067753 | 0.1436914 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0121574 | 0.0488109 | -0.0511395 | -0.0511395 | -0.0482127 | -0.0511395 | 0.0503335 | -0.0511395 | 0.0258813 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2917250 | 0.5262062 | 0.1939779 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0483163 | -0.0511395 | -0.0511395 | 0.0236734 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4820140 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0767686 | 0.0392800 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0594100 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1176202 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0022931 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1469532 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1946177 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0061714 | -0.0511395 | -0.0511395 | 0.0174846 | 0.0363032 | -0.0511395 | 0.1334416 | -0.0511395 | -0.0511395 | 0.0458661 | -0.0348783 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0420818 | -0.0511395 | -0.0511395 | -0.0385742 | -0.0511395 | -0.0511395 | 0.0438630 | 0.0567372 | -0.0511395 | -0.0511395 | 0.0262479 | 0.0674996 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0177008 | -0.0511395 | -0.0511395 | 0.1351902 | 0.0430978 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1381855 | -0.0511395 | -0.0511395 | 0.0326151 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0139021 | -0.0048871 | -0.0511395 | 0.0423518 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0097320 | -0.0511395 | -0.0511395 | 0.0185255 | -0.0511395 | -0.0511395 | 0.1313847 | -0.0511395 | -0.0511395 | 0.1056130 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1329768 | 0.0012274 | -0.0511395 | -0.0511395 | 0.0733332 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0344302 | -0.0511395 | 0.1155010 | 0.0284560 | 0.0022166 | -0.0511395 | 0.0194955 | -0.0333551 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0401669 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1310750 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0462890 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | 0.0162361 | -0.0511395 | -0.0410921 | 0.1586376 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0230457 | 0.1217541 | 0.0142727 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0724156 | -0.0511395 | -0.0511395 | 5.6133504 | 0.2382817 | -0.0511395 | 0.1071806 | -0.0379996 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1233354 | -0.0511395 | -0.0490550 | -0.0511395 | 0.0331080 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | 0.4453194 | 0.0173923 | 0.1355726 | 0.1315628 | -0.0511395 | -0.0511395 | 0.0639548 | -0.0511395 | 0.1846334 | -0.0420014 | 0.0038650 | 0.0576751 | -0.0511395 | -0.0511395 | 0.0180383 | 0.1032727 | -0.0249582 | 0.4418829 | 0.0733426 | 0.0485612 | -0.0511395 | -0.0511395 | -0.0028980 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2058627 | -0.0511395 | -0.0511395 | -0.0391171 | 0.2370961 | 0.0292630 | 0.1056316 | -0.0511395 | 0.0068741 | -0.0381064 | 0.0350461 | -0.0511395 | -0.0337881 | -0.0135199 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0327434 | 0.0445211 | 0.0519365 | -0.0511395 | 0.5189580 | -0.0247287 | 0.0772724 | -0.0511395 | -0.0511395 | -0.0240164 | -0.0511395 | 0.0540167 | 0.0040237 | 0.0655196 | 0.1244534 | 0.1516930 | 0.1468213 | -0.0511395 | 0.0584037 | -0.0511395 | 0.0292630 | -0.0390716 | 0.0393069 | 0.1081511 | 0.0890663 | -0.0511395 | -0.0511395 | 0.0870590 | 0.2071852 | 0.7941945 | -0.0326562 | -0.0511395 | 0.0334948 | 0.0473591 | 0.0637212 | -0.0157329 | 0.1900716 | -0.0122147 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0357821 | -0.0511395 | -0.0511395 | -0.4439859 | 0.0473290 | -0.0511395 | 0.1110463 | -0.0511395 | -0.0511395 | -0.0305338 | -0.0084583 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0285182 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0133513 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0211097 | -0.0511395 | 0.0545181 | -0.0098223 | -0.0511395 | -0.0306718 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0140977 | -0.0511395 | -0.0511395 | 0.0862376 | -0.0699444 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1341945 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0029962 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2332124 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0924530 | -0.0511395 | 0.0827072 | -0.0511395 | -0.0391983 | -0.0511395 | 0.0473631 | 0.0172286 | -0.0343286 | -0.0511395 | 0.1638731 | -0.0511395 | -0.0511395 | 0.0515529 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0063869 | 0.2446661 | -0.0511395 | 0.1237852 | -0.0511395 | -0.0511395 | 0.0020306 | -0.0511395 | -0.0511395 | -0.0064450 | -0.0383714 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1057928 | -0.0511395 | 0.4125008 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0119594 | 0.0161865 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0460585 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0024215 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2291110 | -0.0511395 | -0.0511395 | -0.0180893 | -0.0511395 | -0.0511395 | -0.0266491 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1336102 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0341431 | 0.6162119 | 0.0082133 | -0.0096703 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0287231 | 0.0084997 | 0.0318155 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1443653 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0655201 | 0.0125757 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0223688 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0102347 | -0.0511395 | 0.2738066 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0111747 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0759489 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0969623 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0536467 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0276900 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0444576 | -0.0024504 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1724718 | -0.0066521 | -0.0393006 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0705177 | -0.0511395 | -0.0511395 | -0.0489558 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0983004 | -0.0511395 | -0.0511395 | 0.0661585 | 0.0869817 | -0.0511395 | 0.1152989 | -0.0511395 | 0.0510815 | -0.0511395 | 0.0292293 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0476248 | -0.0511395 | 0.1900681 | 0.0261715 | -0.0511395 | -0.0511395 | -0.0364830 | -0.0511395 | -0.0479683 | -0.0511395 | -0.0254417 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3433160 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.3218275 | -0.0104061 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2626620 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0458545 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0540577 | -0.0379240 | -0.0511395 | -0.0511395 | -0.0360881 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0008934 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0246787 | 0.0481431 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0215125 | -0.0511395 | -0.0350882 | 0.0344917 | 0.0900387 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0570944 | 0.0497963 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1302210 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1055057 | 0.0405596 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1209802 | -0.0511395 | 0.0732776 | -0.0511395 | 0.0095416 | -0.0511395 | -0.0511395 | 0.0199873 | 0.0285886 | -0.0110077 | 0.0964896 | -0.0511395 | -0.0511395 | -0.0096559 | -0.0511395 | 0.0380414 | -0.0511395 | -0.0511395 | 0.0990963 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0630434 | -0.0330464 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1668421 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0015889 | -0.0511395 | -0.0217788 | -0.0511395 | -0.0511395 | 0.1553444 | 0.0110044 | -0.0511395 | -0.0511395 | -0.0365815 | -0.0511395 | -0.0511395 | 0.0529544 | 0.0344058 | -0.0511395 | 0.0261994 | 0.0822625 | -0.0511395 | -0.0511395 | 0.0304092 | 0.3493394 | 0.2893611 | -0.0511395 | 0.0422131 | -0.0511395 | -0.0511395 | 0.1887703 | 0.4229562 | -0.0274450 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0524301 | -0.0511395 | -0.0511395 | 0.1212148 | -0.0511395 | -0.0511395 | 0.1996322 | -0.0511395 | -0.0453353 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0269307 | 0.0172591 | 0.1152077 | -0.0511395 | 0.2664151 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0225234 | 0.0036539 | -0.0428346 | -0.0511395 | -0.0511395 | -0.0099595 | -0.0511395 | 0.1115439 | 0.0799410 | 0.1731943 | 0.5364349 | 0.0300668 | -0.0295539 | 0.0451128 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0825804 | -0.0511395 | -0.0511395 | 0.0903184 | -0.0511395 | -0.0315549 | 0.4525175 | -0.0511395 | 0.1127247 | -0.0511395 | -0.0511395 | -0.0174029 | 0.5478168 | -0.0511395 | 0.7905836 | -0.0511395 | 0.0522278 | -0.0511395 | 0.3707923 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0327485 | -0.0110769 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0445759 | -0.0511395 | 0.0362890 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2262688 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0503322 | -0.0511395 | -0.0511395 | 0.3766649 | -0.0511395 | 0.5441211 | 0.0079853 | 0.0401909 | -0.0511395 | 0.0204040 | 0.0100241 | -0.0511395 | -0.0511395 | 0.0915049 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0382565 | 0.1782678 | 0.2117238 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0395871 | 0.3833477 | -0.0180317 | -0.0511395 | -0.0511395 | -0.0473362 | -0.0511395 | 0.0415721 | -0.0279638 | -0.0076317 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1714408 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0413775 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0052898 | -0.0511395 | -0.0251255 | -0.0511395 | -0.0511395 | -0.0310195 | 0.0284214 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0213204 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0166984 | -0.0511395 | -0.0070090 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0540647 | 0.2536406 | -0.0511395 | 0.0439486 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0034151 | -0.0511395 | -0.0415238 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0428146 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0319896 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0370985 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0924298 | -0.0511395 | 0.0538943 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0421973 | 0.0287157 | -0.0511395 | -0.0511395 | 0.0159847 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0412650 | -0.0511395 | 0.0415390 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2134150 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4209533 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0276506 | -0.0439926 | 0.0748363 | -0.0511395 | 0.0453264 | -0.0511395 | 0.2230880 | -0.0511395 | -0.0511395 | 0.5587184 | 0.3745687 | 0.1364015 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0493532 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1665043 | -0.0511395 | -0.0511395 | -0.0397668 | -0.0165777 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1454193 | -0.0511395 | 0.1548756 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1627297 | -0.0511395 | -0.0511395 | 0.1280494 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0490932 | 0.2869488 | -0.0172263 | -0.0123813 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0183858 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -1.4881601 | 0.1382398 | -0.0321290 | -0.0511395 | -0.0511395 | 0.1879763 | 0.0464253 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1244223 | -0.0511395 | 0.4844383 | 0.0915368 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0890393 | -0.0511395 | 1.0805748 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0436426 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1096656 | -0.0511395 | 0.9973364 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0212501 | -0.0511395 | -0.0511395 | 0.0103535 | -0.0511395 | -0.0511395 | 0.0729995 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0011292 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.5050015 | -0.0256475 | 0.3554967 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1383104 | -0.0058783 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2219792 | -0.0481571 | -0.0511395 | 0.0225738 | -0.0511395 | -0.0511395 | 0.0357621 | -0.0511395 | 0.0041483 | -0.0511395 | -0.0511395 | 0.1184200 | 0.0712224 | -0.0511395 | -0.0511395 | -0.0483332 | -0.0511395 | 0.6249551 | -0.0511395 | -0.0511395 | 0.4118651 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0686656 | -0.0511395 | 0.1900681 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0309840 | 0.0140435 | -0.0511395 | 0.0528347 | 0.0498573 | 0.0547067 | 0.0266121 | -0.0511395 | 0.0363123 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0376685 | -0.0511395 | -0.0511395 | 0.0853481 | -0.0064565 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0007402 | 0.0133574 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0976956 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0243276 | 0.3177571 | 0.0299649 | -0.0478319 | -0.0511395 | 0.0570148 | -0.0511395 | -0.0511395 | 0.0763267 | 0.0084806 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1100254 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0500966 | -0.0511395 | 0.0120866 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.5074883 | -0.0511395 | -0.0511395 | -0.0280446 | -0.0511395 | 0.0929603 | -0.0511395 | 0.0642030 | -0.0511395 | 0.0730376 | 0.0513416 | -0.0511395 | -0.0045977 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0479102 | 0.0348879 | -0.0511395 | -0.0511395 | 0.0217173 | -0.0511395 | 0.3305551 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0545953 | 0.0300268 | -0.0511395 | 0.0606607 | -0.0511395 | 0.0004748 | -0.0339751 | -0.0511395 | -0.0205346 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4409749 | 0.0708272 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1161893 | -0.0449053 | -0.0511395 | 0.0778898 | -0.0511395 | -0.0154111 | 0.1919472 | -0.0395696 | 0.0455649 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0096437 | 0.0413814 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0399379 | -0.0511395 | 0.0201262 | -0.0511395 | -0.0511395 | 0.3022075 | -0.0469952 | -0.0511395 | -0.0388255 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0441497 | 0.1478376 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0621372 | -0.0511395 | -0.0511395 | 0.0237926 | -0.0346461 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0282688 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0506548 | 0.0145910 | -0.0511395 | 0.0722708 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1986524 | -0.0511395 | 0.0930707 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0176118 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0638216 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1391551 | -0.0511395 | 0.1112868 | 0.0241312 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0288914 | -0.0511395 | -0.0511395 | -0.0511395 | 0.6793279 | 0.0084638 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0220871 | -0.0511395 | 0.0512306 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0323160 | -0.0511395 | -0.0018952 | -0.0511395 | -0.0511395 | 0.0681036 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0524951 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0405733 | -0.0511395 | -0.0511395 | -0.0441383 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0500393 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0142455 | -0.0348821 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0308966 | 0.0061408 | -0.0511395 | -0.0511395 | 0.1096230 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0135928 | -0.0511395 | 0.3162106 | -0.0511395 | -0.0511395 | 0.4004696 | -0.0299810 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0296663 | -0.0511395 | -0.0511395 | 0.2294743 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0407251 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0164056 | -0.0511395 | 0.0230860 | -0.0511395 | 0.0058002 | 0.0810409 | 0.0428545 | -0.0511395 | 0.1567632 | 0.1082704 | 0.0704792 | -0.0511395 | 0.1741657 | -0.0511395 | 0.0520508 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0173736 | 0.0191830 | -0.0511395 | 0.2604661 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292394 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1666597 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292291 | -0.0080697 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0156959 | -0.0511395 | 0.0066757 | 0.0496497 | 0.1103809 | -0.0511395 | -0.0511395 | 0.0481042 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1103510 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0410753 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0042941 | -0.0511395 | 0.0447157 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0469086 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1213777 | 0.2886164 | -0.0511395 | 2.5662316 | 0.1047729 | -0.0281674 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4535009 | 0.1340524 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1932239 | -0.0511395 | -0.0511395 | 0.1900739 | 0.0546655 | -0.0511395 | 0.0693362 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0499070 | 0.0614913 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0155602 | 0.0319116 | -0.0511395 | -0.0511395 | 0.0477564 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0304381 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2195118 | -0.0097153 | -0.0511395 | -0.0549081 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0358207 | 0.2425958 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0475355 | 0.0761075 | 0.9295176 | -0.0511395 | -0.0496623 | -0.0511395 | 0.0788537 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0500898 | -0.0511395 | -0.0408408 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1762538 | -0.0511395 | 0.0347252 | -0.0511395 | 0.0174465 | 0.1302080 | -0.0511395 | -0.0259228 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0374932 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2554562 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0498139 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0526359 | 0.1315082 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0502487 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2929774 | 0.0163807 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1039225 | -0.0511395 | 0.0020202 | -0.0511395 | -0.0511395 | 0.0307089 | -0.0511395 | 0.0489625 | -0.0511395 | -0.0281299 | -0.0484303 | -0.0511395 | -0.0511395 | -0.0359860 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0180527 | -0.0511395 | 0.0323181 | -0.0511395 | 0.0296752 | 0.0242379 | -0.0511395 | -0.0511395 | 0.0397818 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0313217 | -0.0511395 | 0.0062747 | -0.0136876 | 0.1519356 | -0.0511395 | -0.0511395 | 0.0813599 | -0.0511395 | -0.0511395 | 0.4123929 | -0.0511395 | 0.1018507 | -0.0511395 | 0.0492713 | 0.0296313 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292709 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2899741 | 0.0671459 | -0.0380117 | 0.0626484 | -0.0063293 | -0.0511395 | -0.0199775 | -0.0511395 | -0.0511395 | 0.2837184 | 0.0001834 | -0.0511395 | -0.0511395 | -0.0373781 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0452802 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1275328 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0099668 | 0.0759219 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0211005 | 0.1504082 | -0.0511395 | 0.0103297 | -0.0511395 | 0.0837984 | -0.0511395 | 0.0292630 | -0.8668838 | -0.0511395 | -0.0371331 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0434726 | -0.0511395 | 0.1661460 | -0.0511395 | -0.0511395 | 0.1965763 | 0.0092496 | 0.0751214 | 0.0213861 | -0.0511395 | 0.0511892 | 0.0697779 | -0.0511395 | 0.0748949 | -0.0191234 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1341094 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1044479 | 0.1131986 | 0.0293862 | -0.0511395 | -0.0511395 | 0.0505034 | 0.2490871 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0801507 | -0.0511395 | -0.0511395 | -0.0301241 | -0.0511395 | 0.0148998 | 0.0305827 | 0.0264836 | -0.0511395 | 0.0077589 | 0.1338364 | 0.0278831 | -0.0335890 | -0.0511395 | 0.0291643 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0260977 | -0.0156525 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0364257 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0996153 | -0.0511395 | -0.0318162 | 0.0012041 | -0.0301252 | -0.0305406 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1831269 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0469238 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0174445 | -0.0511395 | -0.0511395 | 0.0005552 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0412393 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0385420 | 0.0706924 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1603461 | 0.0319122 | -0.0327148 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0246106 | -0.0511395 | -0.0101797 | 0.2171978 | -0.0511395 | 0.0349747 | 0.2588194 | 0.1338791 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1734374 | -0.0511395 | 0.0175646 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0138590 | 0.4492014 | -0.0098672 | -0.0511395 | -0.0111568 | -0.0160203 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0504375 | 0.0279449 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0538229 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0767230 | -0.0511395 | -0.0511395 | 0.0438269 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0701920 | -0.0511395 | -0.0511395 | 0.0545130 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0467458 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0470954 | -0.0511395 | -0.0511395 | -0.0178077 | 0.3416887 | -0.0511395 | -0.0069623 | -0.0511395 | -0.0016094 | -0.0511395 | -0.0418217 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0208040 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2097742 | 0.2673141 | -0.0511395 | 0.1394053 | -0.0511395 | 0.2233517 | -0.0511395 | -0.0511395 | -0.0388781 | -0.0511395 | -0.0511395 | 0.0088103 | -0.0447910 | -0.0511395 | 0.0025948 | -0.0511395 | 0.2744908 | -0.0511395 | -0.0511395 | -0.0356198 | -0.0511395 | 0.0302202 | -0.0483154 | -0.0511395 | -0.0114480 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2854474 | -0.0511395 | -0.0511395 | -0.0448481 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0449139 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0146550 | 0.0302404 | -0.0048772 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0413612 | -0.0236693 | -0.0511395 | -0.0511395 | 0.0004584 | -0.0511395 | -0.0511395 | 0.3078801 | -0.0511395 | -0.0511395 | 0.1264154 | -0.0511395 | -0.0511395 | 0.0039261 | -0.0511395 | 0.0914935 | -0.0511395 | -0.0275290 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0364884 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0030263 | 0.0143808 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0738982 | -1.2039024 | -0.0222373 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0931667 | -0.0511395 | -0.0511395 | 0.1555664 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0184803 | -0.0511395 | -0.0335729 | -0.0511395 | -0.0014806 | -0.0511395 | -0.0511395 | 0.0330203 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0439992 | -0.0511395 | -0.0511395 | -0.1322000 | 0.0718457 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0454362 | 0.1455284 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0626380 | -0.0511395 | -0.0511395 | -0.0051805 | -0.0511395 | -0.0511395 | -0.0350590 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0011840 | 0.0197769 | 0.0700269 | -0.0511395 | 0.0426936 | 0.3319035 | -0.0097865 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0497684 | -0.0421712 | -0.0196169 | -0.0511395 | -0.0511395 | -0.0251449 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0493736 | -0.0511395 | 0.0986192 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0064914 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0234230 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1256583 | -0.0511395 | 0.0450077 | 0.2870579 | 0.0463191 | -0.0200891 | -0.0511395 | 0.0448175 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0741758 | -0.0511395 | -0.0511395 | -0.0231837 | -0.0511395 | -0.0511395 | -0.0259869 | -0.0511395 | -0.0511395 | 0.0372024 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0423251 | -0.0511395 | -0.0388988 | 0.0367550 | -0.0511395 | -0.0511395 | 0.0292630 | 0.0251320 | 0.0667528 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1432238 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0304524 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0453465 | -0.0511395 | -0.0511395 | 0.0753712 | -0.0511395 | -0.0327858 | -0.0162072 | -0.0086272 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0161418 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0134541 | 0.0331105 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4110683 | 0.0095455 | -0.0511395 | -0.0511395 | 0.0943396 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0851270 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2659446 | -0.0352900 | -0.0511395 | 0.0138256 | -0.0511395 | -0.0511395 | -0.0127903 | -0.0215072 | 0.0318065 | -0.0511395 | -0.0511395 | 0.1982444 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0217837 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2055497 | -0.0511395 | -0.0511395 | -0.1375816 | -0.0511395 | 0.1517047 | -0.0511395 | -0.0348403 | 0.3995100 | -0.0511395 | -0.0511395 | 0.0396957 | -0.0232734 | -0.0511395 | 0.0058258 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0004533 | -0.0511395 | -0.0511395 | -0.0277762 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4804038 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0437705 | 0.0104749 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0524352 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0421260 | -0.0511395 | 0.0671014 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0532677 | 0.0483831 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0344655 | 0.1420474 | -0.0511395 | 0.1521656 | -0.0413577 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0492730 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0142599 | 0.0635685 | -0.0511395 | 0.0016704 | 0.0521236 | -0.0511395 | -0.0094798 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1196394 | -0.0511395 | 0.0119734 | 0.1074845 | 0.0885994 | -0.0511395 | 0.2307452 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0418745 | -0.0511395 | -0.0511395 | -0.0433463 | -0.0511395 | 0.0692746 | -0.0648030 | -0.0219800 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1424303 | -0.0345045 | 0.0648779 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0548446 | -0.0511395 | -0.0511395 | -0.0353698 | -0.0030539 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0121822 | -0.0255937 | 0.0292630 | -0.0511395 | -0.0511395 | 0.2366208 | -0.0511395 | -0.0298515 | -0.0511395 | -0.0086842 | 0.1356337 | -0.0511395 | -0.0324367 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0255865 | -0.0511395 | -0.0433622 | -0.0511395 | 0.1542617 | -0.0511395 | -0.0511395 | -0.0144933 | 0.0778041 | -0.0129236 | -0.0511395 | -0.0511395 | 0.0462189 | -0.0511395 | 0.0247692 | -0.0511395 | -0.0226117 | -0.0511395 | 0.0061270 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0003359 | -0.0511395 | -0.0511395 | 0.0694643 | 0.0314991 | -0.0352520 | -0.0511395 | 0.0706193 | -0.0433670 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0669244 | -0.0511395 | -0.0511395 | -0.0140067 | -0.0147794 | -0.0511395 | 0.1297767 | -0.0511395 | -0.0511395 | -0.0423482 | -0.0511395 | 0.0466951 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1922376 | -0.0511395 | -0.0511395 | 0.0089739 | -0.0511395 | -0.0511395 | 0.1522742 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2189723 | -0.0191462 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0419312 | -0.0511395 | 0.0525001 | -0.0511395 | -0.0511395 | -0.0470853 | -0.0511395 | -0.0511395 | 0.0851486 | 2.5264629 | 0.0391845 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0166578 | -0.0511395 | 0.2220669 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0138097 | -0.0511395 | -0.0511395 | -0.0422785 | 0.0486104 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3857158 | -0.0511395 | -0.0511395 | 0.0767881 | -0.0511395 | -0.0511395 | -0.0023525 | -0.0144470 | -0.0158551 | 0.0876707 | -0.0511395 | -0.0511395 | 0.0400037 | -0.0511395 | -0.0461090 | 0.0261942 | -0.0511395 | -0.0511395 | 0.0646048 | -0.0511395 | -0.0484026 | -0.0511395 | -0.0511395 | 0.0083823 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1771556 | -0.0129177 | -0.0511395 | 0.0838700 | -0.0511395 | 0.1274945 | -0.0511395 | 0.1309830 | -0.0118248 | -0.0511395 | 0.1053784 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0231677 | 0.0325199 | -0.0511395 | 0.0870413 | -0.0511395 | 0.2459181 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0932840 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0257745 | 0.0951377 | 0.0248940 | -0.0511395 | 0.0881778 | 0.0664459 | -0.0511395 | -0.0511395 | 0.1328936 | -0.0511395 | 0.0359126 | -0.0461156 | -0.0511395 | 0.0260185 | -0.0511395 | -0.0511395 | 0.6327645 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0178606 | -0.0511395 | -0.0511395 | -0.0271593 | -0.0511395 | 0.0667121 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1669692 | -0.0511395 | 0.0664474 | -0.0511395 | -0.0291214 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0381954 | -0.0511395 | -0.0511395 | 0.1000568 | -0.0511395 | -0.0511395 | 0.0025474 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0606396 | -0.0300996 | -0.0511395 | -0.0511395 | 0.0934625 | -0.0511395 | -0.0511395 | 0.0541475 | 0.1338639 | 0.1496688 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0969157 | -0.0129293 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0047856 | 0.0678123 | -0.0133835 | -0.0511395 | -0.0511395 | 0.1257306 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0362164 | -0.0376213 | -0.0511395 | -0.0511395 | 0.2011283 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1292559 | -0.0431452 | 0.0486437 | -0.0511395 | -0.0230956 | -0.0511395 | -0.0176006 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0142690 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0478806 | -0.0511395 | 0.0569226 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0366972 | -0.0172731 | 0.0212855 | -0.0511395 | -0.0511395 | 0.0212160 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0567464 | -0.0511395 | -0.0511395 | 0.1338674 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1212942 | -0.0232434 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0285358 | 0.0972814 | -0.0423814 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0271957 | -0.0511395 | 0.0485153 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0106479 | -0.0027288 | -0.0511395 | -0.0511395 | 0.0095660 | -0.0511395 | -0.0438207 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0599326 | -0.0511395 | -0.0158130 | -0.0511395 | -0.0511395 | 0.0032091 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0004477 | 0.0664670 | -0.0011552 | -0.0511395 | -0.0250032 | 0.1758584 | -0.0511395 | 0.2153538 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0769562 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292460 | -0.0236617 | -0.0511395 | 0.0020411 | -0.0511395 | -0.0511395 | 0.0909747 | -0.0511395 | -0.0357597 | 0.0213303 | 0.0213433 | 0.0668462 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1027936 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0263841 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0417477 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3163967 | -0.0511395 | 0.0590826 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3233990 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0164197 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | 0.0243623 | -0.0511395 | -0.0323789 | 0.2125750 | -0.0511395 | 0.2676286 | 0.0000257 | 0.0431998 | -0.0511395 | 0.0872050 | -0.0298181 | -0.0187788 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0211832 | -0.0022154 | -0.0511395 | -0.0316873 | -0.0511395 | 0.0361218 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0417946 | -0.0702552 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0219384 | -0.0511395 | -0.0397733 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1242950 | -0.0511395 | -0.0511395 | 0.1155625 | 0.0564716 | -0.0511395 | -0.0511395 | -0.0055111 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0091624 | -0.0511395 | -0.0511395 | 0.1416919 | -0.0511395 | -0.0511395 | 0.0394664 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0109383 | -0.0511395 | -0.0511395 | 0.0021450 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0213672 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0349514 | 0.3208025 | 0.0022714 | 0.2411433 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1697556 | -0.0511395 | -0.0511395 | 0.0669893 | 0.3007292 | -0.0511395 | -0.0511395 | -0.1053980 | -0.0511395 | 0.0313193 | -0.0279508 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0302326 | -0.0252002 | -0.0488322 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1489414 | -0.0511395 | -0.0511395 | -0.0289499 | 0.1782907 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0107800 | -0.0511395 | -0.0511395 | 0.0300941 | -0.0511395 | 0.0060292 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2304002 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0003322 | -0.0511395 | -0.0511395 | -0.0228595 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0507745 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0038394 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0904812 | 0.0087723 | -0.0511395 | 0.2539218 | -0.0511395 | 0.0327075 | -0.0511395 | 0.0190823 | 0.0051466 | -0.0511395 | -0.0511395 | -0.0051023 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0308270 | -0.0380329 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0341742 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0894273 | -0.0511395 | -0.0511395 | 1.0058599 | 0.1301046 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1410426 | -0.0511395 | -0.0511395 | 0.1993340 | -0.0442061 | -0.0511395 | 0.0117441 | 0.0911971 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0150383 | -0.0511395 | 0.1379713 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0847557 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0114981 | -0.0511395 | -0.0479020 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0006926 | -0.0511395 | 0.0116336 | -0.0511395 | 0.0673778 | 0.0040809 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0062909 | 0.0036198 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0258356 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0264169 | -0.0511395 | 0.1775404 | -0.0511395 | -0.0511395 | 0.0443000 | -0.0511395 | 0.2137447 | -0.0511395 | 0.2099962 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0787372 | -0.0511395 | 0.1841779 | 0.1027094 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0609054 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2129417 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0075880 | -0.0511395 | -0.0419019 | 0.1207206 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.7002247 | -0.0511395 | -0.0511395 | 0.3504245 | 0.1358192 | -0.0511395 | -0.0511395 | 0.1115060 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0309117 | 0.1995266 | 0.0101650 | 0.0596168 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0113704 | -0.0505936 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3862098 | 0.2592558 | -0.0511395 | -0.0511395 | 0.2559971 | -0.0511395 | -0.0203063 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1174966 | -0.0511395 | -0.0511395 | 0.0495711 | 0.8399170 | -0.0511395 | -0.0511395 | 0.2323088 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1487576 | -0.0511395 | -0.0492878 | -0.0055434 | -0.0126778 | -0.0279463 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0739029 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2666591 | 0.1049311 | -0.0511395 | -0.2029645 | -0.0511395 | -0.0511395 | 0.5204254 | -0.0511395 | -0.0511395 | 0.0816177 | 0.0883156 | -0.0511395 | 0.0041856 | 0.0601173 | -0.0054973 | -0.0511395 | -0.0511395 | -0.0130541 | 0.0380654 | 0.5844735 | 0.1674943 | -0.0511395 | 0.2402734 | -0.0511395 | 0.0346575 | -0.0511395 | -0.0511395 | -0.0006368 | -0.0511395 | 0.0005987 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3111992 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1562466 | -0.0511395 | -0.0210099 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0243765 | -0.0511395 | -0.0318245 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0365235 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1051273 | -0.0511395 | 0.0625491 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0868694 | -0.0511395 | -0.0511395 | 0.0283150 | -0.0464738 | -0.0511395 | -0.0511395 | -0.0271912 | -0.0111200 | 0.1728349 | -0.0511395 | -0.0511395 | 0.0349062 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0178314 | -0.0511395 | -0.0511395 | 0.0339481 | -0.0511395 | 0.1090435 | -0.0511395 | -0.0053296 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0179617 | -0.0511395 | 0.2192124 | -0.0044112 | -0.0424351 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0391675 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0381155 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0154695 | -0.0511395 | -0.0511395 | 0.0142460 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0796061 | -0.0511395 | -0.0511395 | -0.0346380 | -0.0511395 | -0.0511395 | 0.0421482 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0117659 | -0.0511395 | -0.0511395 | 0.0555808 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0465218 | -0.0511395 | 0.0899321 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0197900 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0530869 | -0.0511395 | 0.0292630 | 0.0434767 | 0.0338079 | -0.0511395 | -0.0511395 | 0.0731177 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0362191 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1112946 | -0.0511395 | 0.1728879 | 0.0345230 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0532024 | 0.2216689 | 0.1503104 | 0.0117873 | -0.0511395 | -0.0392538 | 0.0657400 | 0.0765035 | 0.0292630 | -0.0511395 | -0.0511395 | 0.1237096 | -0.0511395 | -0.0511395 | 0.0580300 | -0.0511395 | 0.0136811 | -0.0511395 | -0.0511395 | 0.1760407 | -0.0511395 | 0.0962994 | 0.1301823 | -0.0509750 | -0.0511395 | -0.0162786 | -0.0511395 | 0.1318562 | -0.0400198 | -0.0511395 | 0.1947735 | -0.0511395 | -0.0511395 | -0.0482690 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0605395 | 0.0721825 | 0.4675586 | -0.0511395 | -0.0511395 | 0.0032829 | 0.0975304 | 0.2640309 | -0.0511395 | -0.0511395 | 0.1248530 | 0.1667158 | 0.0114852 | 0.0292630 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0405711 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0305704 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0407634 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0260476 | 0.0164429 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0235246 | -0.0511395 | -0.0511395 | -0.0181980 | -0.0511395 | -0.0511395 | -0.0174110 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0365209 | 0.0876396 | -0.0511395 | 0.0772056 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2137126 | -0.0511395 | 0.0290061 | -0.0511395 | -0.0045422 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0324413 | -0.0511395 | -0.0511395 | 0.0679687 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1776195 | -0.0511395 | -0.0511395 | -0.0209298 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511261 | 0.2507845 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0563326 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0735360 | -0.0511395 | -0.0511395 | -0.0261377 | -0.0511395 | -0.0511395 | -0.0105409 | -0.0511395 | 0.0649382 | -0.0511395 | -0.0511395 | 0.0492148 | 0.0606556 | 0.1209416 | -0.0511395 | -0.0511395 | 0.0365546 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0157111 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0281670 | -0.0511395 | 0.0526821 | -0.0511395 | -0.0012641 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0296695 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0837140 | -0.0511395 | -0.0404428 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0251021 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0198853 | -0.0511395 | -0.0479218 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0550458 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0008411 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0333100 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2611217 | 0.1116181 | 0.3131802 | -0.0511395 | -0.0511395 | 0.0399681 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0454752 | -0.0511395 | -0.0511395 | -0.0035626 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1566063 | 0.1046456 | -0.0511395 | 0.0400999 | -0.0241531 | 0.1076497 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0293178 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1047086 | -0.0511395 | 0.0422676 | 0.0046510 | -0.0511395 | -0.0511395 | 0.0233331 | -0.0511395 | -0.0160381 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0484171 | 0.0291856 | -0.0511395 | -0.0441731 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0472686 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0040683 | 0.0768592 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0500946 | 0.0907005 | -0.0511395 | -0.0511395 | 0.0292630 | 0.0765306 | -0.0511395 | -0.0041216 | -0.0327803 | -0.0457794 | -0.0511395 | -0.0279735 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0560638 | -0.0511395 | -0.0402923 | 0.3871425 | -0.0511395 | -0.0356880 | -0.0511395 | -0.0511395 | -0.3114141 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0843367 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1276281 | 0.0712825 | -0.0340125 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0167083 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0653497 | 0.0694643 | -0.0511395 | -0.0511395 | -0.0102496 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0229615 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1107936 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0128440 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0023311 | -0.0511395 | 0.1007944 | -0.0085781 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0016010 | -0.0511395 | -0.0511395 | -0.0258420 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0409568 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0882705 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0350311 | 0.2012627 | -0.0511395 | 0.0859305 | 0.0607889 | -0.0511395 | -0.0511395 | 0.0447956 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0276226 | -0.0282322 | -0.0511395 | 0.0381652 | -0.0511395 | -0.0220035 | -0.0511395 | 0.0188341 | -0.0511395 | 0.0229345 | 0.2027365 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0713985 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2296440 | -0.0331085 | -0.0511395 | -0.0511395 | 0.0600090 | 0.0575394 | -0.0511395 | 0.0663178 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1575176 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2693583 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1556683 | -0.0072271 | -0.0511395 | -0.0511395 | -0.0025762 | 0.0193433 | 0.0432204 | -0.0511395 | -0.0511395 | -0.0058913 | 0.1929899 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0314419 | -0.0511395 | 0.3695579 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1374293 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0447231 | -0.0234835 | 0.0218897 | -0.0511395 | -0.0590943 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1230094 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0152706 | -0.0511395 | 0.0476814 | -0.0511395 | -0.0511395 | -0.0531192 | -0.0391032 | 0.0088081 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1947764 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0204461 | -0.0511395 | 0.1099800 | -0.0049118 | -0.0511395 | -0.0511395 | -0.0913911 | -0.0511395 | -0.0511395 | -0.0511395 | -0.1145540 | -0.0308525 | 0.0545823 | -0.0286945 | -0.0511395 | -0.0489929 | -0.0511395 | 0.3626595 | -0.0511395 | -0.0511395 | 0.0374380 | 0.0150472 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1117653 | 0.0431239 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0046779 | -0.0511395 | -0.0511395 | 0.1041443 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0933291 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0275042 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1818017 | -0.0511395 | -0.0511395 | -0.0324078 | -0.0511395 | 0.0196936 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0264540 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0429679 | -0.0173732 | -0.0125823 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0370471 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0485520 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0712883 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1845135 | -0.0511395 | 0.0381574 | -0.0511395 | -0.0511395 | 0.0709582 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0729567 | -0.0511395 | -0.0354174 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2339771 | -0.0511395 | -0.0511395 | 0.0214363 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0351553 | -0.0511395 | 0.0923340 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0948448 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0511395 | -0.0511395 | 0.0737391 | -0.0511395 | -0.0090994 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0281293 | -0.0511395 | -0.0511395 | 0.0442509 | -0.0309611 | 0.0220495 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0235140 | 0.0127790 | 0.0319772 | -0.0511395 | -0.0511395 | 0.0312667 | -0.0511395 | -0.0206330 | -0.0511395 | 0.0533640 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0508886 | 0.0055030 | -0.0511395 | -0.0122602 | -0.0208110 | 0.1012824 | -0.0511395 | -0.0511395 | 0.1202252 | -0.0511395 | -0.0414263 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0079351 | -0.0463225 | -0.0511395 | 0.0292630 | -0.0232333 | 0.0790483 | 0.2446838 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0353527 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0213643 | 0.0215973 | -0.0314382 | -0.0511395 | -0.0511395 | -0.0247412 | -0.0511395 | 0.1272027 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0138646 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3373338 | -0.0511395 | -0.0511395 | 0.0867894 | -0.0454570 | 0.2882947 | 0.0633888 | 0.2060916 | -0.0511395 | -0.0511395 | 0.1496637 | -0.0511395 | -0.0511395 | 0.1549214 | -0.0511395 | -0.0511395 | -0.0355970 | -0.0511395 | -0.0511395 | -0.0066499 | -0.0511395 | 0.0589556 | 0.0013717 | -0.0364270 | -0.0511395 | -0.0511395 | -0.0081173 | -0.0511395 | -0.0084927 | -0.0511395 | -0.0511395 | 0.2853847 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0144174 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0125463 | 0.0498605 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0244458 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0080937 | -0.0511395 | 0.0701074 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1290498 | -0.0511395 | 0.0453435 | -0.0511395 | 0.0317497 | -0.0511395 | 0.0978659 | -0.0511395 | -0.0511395 | 0.1008917 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1065576 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0366044 | 0.0515193 | 0.0059972 | -0.0511395 | -0.0511395 | 0.0421072 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0464996 | 0.2735976 | 0.4305368 | 0.1355168 | -0.0511395 | -0.0511395 | 0.0750714 | -0.0511395 | -0.0511395 | -0.0511395 | 2.3754821 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0213436 | 0.0544644 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0760509 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0104188 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0366490 | 0.0837896 | 0.2254888 | -0.0511395 | -0.0511395 | -0.0511395 | 0.6797796 | 0.4939417 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0457582 | 0.2098623 | -0.0511395 | 0.1100548 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0631311 | 0.0213082 | 0.0158597 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0556699 | 0.1163648 | 0.2444351 | 0.0759062 | 0.3196010 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.5825829 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0232372 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0010015 | -0.0511395 | 0.0296253 | -0.0511395 | -0.0511395 | 0.0093816 | 0.0783979 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0316185 | -0.0453180 | 0.0111824 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0504009 | 0.1379832 | 0.0228193 | -0.0511395 | 0.1257323 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0460674 | 0.0300132 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0046787 | -0.0321157 | -0.0511395 | 0.0074992 | -0.0511395 | -0.0511395 | 0.0883692 | 0.1067970 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0375302 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0118789 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4121466 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.3304183 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0212755 | 0.0250011 | -0.0086562 | -0.0511395 | 0.0298225 | 0.0370618 | -0.0511395 | -0.0311822 | -0.0511395 | -0.0105299 | -0.0511395 | 0.0426468 | 0.2636968 | 0.2547182 | 0.8960042 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0758428 | 0.1089602 | -0.0511395 | 0.2853933 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0153715 | -0.0511395 | 0.3265641 | 0.2748946 | 0.0835905 | -0.0719662 | -0.0511395 | 0.0524580 | -0.0511395 | -0.0511395 | 0.1280726 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0036182 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1957975 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2267959 | -0.0511395 | -0.0511395 | -0.0052310 | -0.0485811 | -0.0511395 | -0.0448733 | 0.0454590 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2190415 | -0.0511395 | 0.0071215 | -0.0511395 | -0.0511395 | -0.0511395 | 0.5227399 | 0.2530306 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4738008 | 0.1322976 | 0.2927560 | 0.0683473 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4646796 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.4927081 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0190944 | 0.1833511 | -0.0511395 | 0.5200903 | -0.0511395 | 0.2057359 | -0.0511395 | -0.0511395 | 0.0349217 | -0.0151027 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.2807613 | -0.0494177 | 0.0730440 | -0.0511395 | -0.0139164 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0148026 | 0.1350959 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1368078 | 0.0494818 | -0.0511395 | 0.0246690 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.8181577 | 0.6230598 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0432755 | -0.0420897 | -0.0511395 | 0.8073837 | -0.0511395 | 0.0353065 | -0.0511395 | -0.0511395 | 0.0105136 | -0.0511395 | -0.0511395 | -0.0019837 | -0.0087286 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1314184 | -0.0511395 | 0.0519155 | 0.3130577 | -0.0083158 | 0.1426249 | -0.0511395 | 0.0899732 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0547484 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0992763 | 0.0013512 | -0.0511395 | -0.0227456 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.1109747 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0117252 | -0.0511395 | -0.0511395 | 0.0292630 | -0.0355778 | -0.0511395 | -0.0511395 | 0.3879747 | 0.0235451 | 0.0663041 | -0.0511395 | -0.0511395 | 0.0045143 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0626761 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | -0.0511395 | 0.0320511 |
| Max_201308 | -0.0248850 | 0.0126459 | -0.0125401 | 0.0074599 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0256481 | 0.0033035 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0218928 | 0.0382086 | -0.0269110 | 0.0555021 | -0.0269110 | -0.0061040 | -0.0207295 | 0.0386482 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0359660 | -0.0269110 | 0.1486024 | 0.0076807 | -0.0095223 | -0.3658734 | 0.0168251 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0091668 | 0.0290700 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0046281 | -0.0269110 | -0.0261406 | -0.0269110 | -0.0269110 | 0.0052485 | -0.0269110 | -0.0269110 | -0.0247248 | -0.0269110 | -0.0269110 | -0.0061701 | -0.0269110 | -0.0261719 | -0.0269110 | -0.0269110 | -0.0104690 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0215651 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0198642 | -0.0269110 | -0.0240355 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0204818 | -0.0235119 | 0.0099529 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0007033 | 0.0185983 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0207560 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0075888 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0042001 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0121192 | 0.0001138 | 0.0208583 | -0.0269110 | -0.0269110 | 0.0186196 | -0.0269110 | 0.0085718 | 0.0046864 | 0.0711524 | -0.0269110 | -0.0269110 | -0.0068164 | -0.0269110 | 0.0057266 | -0.0195373 | -0.0269110 | 0.0199790 | 0.0297005 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0047902 | -0.0197968 | -0.0269110 | -0.0092447 | -0.0027240 | -0.0269110 | 0.0100645 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0030404 | 0.0600098 | -0.0269110 | 0.0151954 | -0.0269110 | -0.0126557 | -0.0269110 | 0.0398425 | 0.0028063 | -0.0269110 | 0.0557098 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0037506 | 0.0066058 | 0.0253231 | -0.0269110 | -0.0269110 | -0.0046961 | -0.0108313 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0541633 | -0.0269110 | -0.0269110 | 0.0218567 | 0.0245606 | 0.0726946 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0194433 | 0.0044724 | -0.0269110 | -0.0269110 | 0.0898636 | -0.0071243 | 0.0058463 | -0.0269110 | 0.0225996 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0144954 | 0.0029027 | -0.0269110 | -0.0269110 | 0.0137479 | -0.0269110 | -0.0269110 | -0.0050442 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0003417 | 0.0223947 | 0.0466768 | -0.0081118 | 0.0089583 | 0.0091220 | 0.0128494 | -0.0269110 | -0.0099997 | -0.0269110 | 0.0235150 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0248486 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0196032 | -0.0039609 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0832676 | -0.0269110 | 0.0010083 | -0.0126015 | 0.0034919 | 0.0254860 | -0.0269110 | -0.0269110 | -0.0054125 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0213969 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 73.9041392 | -0.0269110 | -0.0162995 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0058633 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0109642 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0144180 | -0.0269110 | -0.0069594 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0758127 | -0.0269110 | -0.0067433 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0164838 | -0.0148171 | -0.0269110 | -0.0213042 | -0.0111683 | -0.0269110 | -0.0269110 | -0.2061135 | 0.0123101 | 0.0094596 | -0.0269110 | -0.0269110 | 0.0129134 | -0.0269110 | 0.0102438 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0098765 | -0.0220558 | -0.0269110 | -0.0281998 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0082174 | -0.0269110 | -0.0193725 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0689528 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0038019 | -0.0269110 | -0.0269110 | -0.0209754 | 0.0097649 | -0.0269110 | -0.0269110 | 0.0255627 | 0.0102365 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0134256 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0060138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0099608 | -0.0269110 | -0.0269110 | 0.0093483 | -0.0249064 | -0.0269110 | -0.0269110 | 0.0219869 | -0.0269110 | -0.0137192 | -0.0269110 | -0.0095277 | -0.0254406 | -0.0269110 | 0.0008550 | -0.0269110 | -0.0152001 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0037211 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0968065 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | 0.0082838 | -0.0269110 | -0.0269110 | 0.0352741 | -0.0269110 | -0.0269110 | 0.0159686 | -0.0269110 | 0.0220379 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0170713 | -0.0269110 | -0.0269110 | -0.0009441 | -0.0269110 | -0.0018213 | -0.0269110 | -0.0269110 | 0.0136799 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0375625 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0008564 | -0.0269110 | 0.0048828 | 0.0007258 | -0.0269110 | -0.0205826 | -0.0269110 | 0.2087932 | -0.0269110 | -0.0105458 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0381576 | -0.0269110 | -0.0269110 | -0.0150801 | -0.0269110 | -0.0269110 | 0.0361788 | -0.0269110 | -0.0128952 | -0.0012208 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0257654 | -0.0269110 | -0.0269110 | 0.0177916 | -0.0269110 | -0.0720056 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0085891 | 0.0190613 | -0.0031674 | -0.0194358 | -0.0269110 | 0.0001138 | -0.0269110 | 0.0001138 | 0.0334811 | 0.0419756 | -0.0269110 | -0.0031581 | -0.0269110 | 0.0534852 | -0.0203506 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0505182 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0215576 | -0.0269110 | 0.1385980 | -0.0108249 | -0.0269110 | 0.0001138 | -0.0208118 | 0.0158479 | 0.0075826 | -0.0038762 | -0.0269110 | -0.0269110 | 0.0236432 | -0.0072652 | -0.0269110 | 0.0209094 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1055356 | -0.0269110 | -0.0053822 | -0.0269110 | -0.0269110 | 0.0068931 | -0.0269110 | 0.0416026 | -0.0269110 | -0.0269110 | -0.0247753 | -0.0269110 | -0.0269110 | 0.0910228 | -0.0127289 | 0.0045200 | -0.0269110 | -0.0269110 | 0.0098313 | -0.0269110 | 0.1835722 | 0.0119311 | -0.0124267 | 0.1266062 | -0.0269110 | -0.0269110 | 0.2767644 | -0.0269110 | -0.0269110 | -0.0420230 | 0.0135180 | -0.0269110 | -0.0269110 | -0.0041518 | -0.0269110 | -0.0097818 | -0.0163581 | -0.0269110 | 0.0791884 | -0.0269110 | -0.0269110 | 0.0176163 | -0.0269110 | -0.0269110 | 0.0418093 | 0.0025720 | -0.0056188 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0213173 | -0.0269110 | -0.0033481 | -0.0269110 | -0.0048173 | -0.0269110 | 0.0613598 | 0.2413374 | -0.0132433 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0191896 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0252656 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0293092 | 0.0129150 | -0.0269110 | 0.1256620 | -0.0269110 | -0.0198540 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0088156 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0110749 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0772250 | -0.0269110 | 0.0472186 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0064317 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0102904 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0196427 | -0.0142769 | 0.0084908 | -0.0269110 | -0.0098730 | -0.0269110 | -0.0119744 | -0.0269110 | 0.0028614 | -0.0269110 | -0.0269110 | -0.0066049 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0245626 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0025505 | -0.0269110 | -0.0115283 | -0.0063950 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0047517 | -0.0103026 | -0.0269110 | -0.0269110 | 0.0436465 | -0.0269110 | -0.0118220 | -0.0269110 | 0.1260503 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0230388 | -0.0244068 | -0.0269110 | 0.0229992 | 0.2233804 | -0.0269110 | -0.0269110 | -0.0195701 | -0.0251923 | -0.0269110 | 0.0347695 | -0.0161097 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0073963 | -0.0269110 | -0.0269110 | -0.0235200 | -0.0269110 | -0.0269110 | -0.0090395 | -0.0269110 | -0.0269110 | -0.0214165 | -0.0269110 | -0.0108568 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0180488 | -0.0150186 | -0.0269110 | -0.0269110 | -0.0124814 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0058123 | 0.0307055 | -0.0269110 | -0.0269110 | -0.0125028 | 0.0192082 | -0.0269110 | -0.0269110 | -0.0005508 | -0.0269110 | -0.0269110 | -0.0254461 | -0.0269110 | -0.0269110 | -0.0193828 | -0.0269110 | -0.0182799 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0548868 | -0.0269110 | -0.0269110 | -0.0086545 | 0.0347455 | 0.0072575 | -0.0269110 | -0.0125327 | -0.0231953 | -0.0269110 | 0.0154209 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0245293 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0212469 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0050145 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0024080 | -0.0269110 | -0.0269110 | 0.0531696 | 0.0016597 | 0.0201876 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0114671 | -0.0124910 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0003994 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0185704 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0194533 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0125548 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0143928 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0407425 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0061741 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0472958 | -0.0269110 | -0.0257844 | -0.0269110 | 0.0082098 | 0.0391756 | 0.0108632 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0298789 | 0.0049923 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0206302 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001123 | -0.0143943 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0195140 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0571836 | 0.0001149 | 0.0001990 | -0.0251832 | -0.0269110 | -0.0081677 | -0.0269110 | 0.0014837 | -0.0269110 | -0.0269110 | -0.0269110 | -0.1079852 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0069262 | -0.0269110 | -0.0100205 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0170161 | -0.0269110 | -0.0246116 | 0.0001138 | -0.0213493 | 0.0621614 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0112192 | 0.0005292 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0192417 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0121669 | -0.0269110 | 0.0594499 | -0.0269110 | 0.0029450 | -0.0269110 | -0.0269110 | 0.0206265 | -0.0269110 | -0.0016076 | -0.0269110 | -0.0269110 | -0.0269110 | 0.2081381 | -0.0269110 | -0.0269110 | -0.0037469 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0075826 | -0.0202323 | -0.0269110 | -0.0269110 | -0.0056089 | -0.0041251 | 0.0938925 | 0.0288893 | -0.0060501 | -0.0079349 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0222881 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0033198 | -0.0269110 | -0.0269110 | 0.0130250 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0129040 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0120720 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0133400 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0147773 | -0.0269110 | 0.0015597 | -0.0269110 | 0.0102306 | -0.0204336 | -0.0269110 | -0.0269110 | 0.0039107 | -0.0269110 | -0.0269110 | -0.0143338 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0963626 | 0.0226786 | -0.0141075 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0219297 | -0.0269110 | -0.0269110 | 0.0177525 | 0.0028880 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0129676 | 0.0468310 | -0.0269110 | -0.0269110 | 0.0362102 | -0.0269110 | -0.0269110 | -0.0256245 | -0.0269110 | -0.0159046 | 0.0847270 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0209029 | -0.0269110 | 0.0534570 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0087117 | 0.0008424 | -0.0269110 | -0.0269110 | -0.0235973 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0356363 | -0.0269110 | 0.0080769 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0312107 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0102359 | -0.0171947 | -0.0246734 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0213628 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0186885 | -0.0269110 | -0.0269110 | -0.0120014 | 0.0066125 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0920842 | 0.3087385 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0114355 | 0.0052312 | -0.0269110 | -0.0235389 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0045247 | 0.0202915 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0227623 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0075688 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0046963 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0247298 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0095752 | -0.0269110 | -0.0065963 | -0.0173440 | 0.0722395 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0166015 | -0.0269110 | -0.0269110 | 0.0096136 | -0.0254793 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0044403 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0237285 | -0.0269110 | -0.0269110 | 0.0156248 | -0.0269110 | -0.0269110 | 0.0211636 | -0.0269110 | -0.0269110 | 0.2005519 | 0.0062265 | -0.0269110 | -0.0160126 | -0.0269110 | -0.0269110 | 0.0211832 | -0.0269110 | -0.0168067 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0521386 | -0.0147068 | -0.0029091 | -0.0092190 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0255174 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0218817 | 0.0670990 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0236116 | 0.0021931 | 0.3011859 | 0.0541268 | -0.0269110 | -0.0261571 | -0.0131371 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0154437 | 0.0213450 | -0.0269110 | 0.0131613 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0334858 | -0.0269110 | 0.0289790 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0843284 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0007074 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0204345 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0088491 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0007870 | -0.0269110 | -0.0269110 | -0.0018144 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0044811 | -0.0223536 | -0.0269110 | 0.0002830 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0270507 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0125841 | 0.0078448 | 0.0472496 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0060032 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0099807 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0501473 | -0.0226469 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0052703 | 0.1316366 | -0.0221810 | -0.0269110 | -0.0269110 | -0.0221028 | 0.0526390 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0558672 | -0.0039378 | -0.0109221 | -0.0269110 | -0.0269110 | 0.0154318 | 0.0753898 | -0.0269110 | -0.0269110 | 0.0102846 | -0.0269110 | -0.0269110 | -0.0234695 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0245160 | -0.0269110 | -0.0269110 | -0.0262123 | -0.0269110 | 0.0541633 | -0.0059039 | 0.0775151 | -0.0195951 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0598204 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0022618 | -0.0269110 | -0.0212574 | -0.0269110 | 0.0102363 | -0.0269110 | -0.0269110 | 0.0914807 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0333176 | -0.0269110 | 0.0003426 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0095303 | 0.0251127 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1157350 | -0.0269110 | -0.0269110 | 0.0178818 | -0.0269110 | -0.0248398 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.2162018 | -0.0269110 | 0.0306363 | -0.0269110 | -0.0268385 | -0.0269110 | -0.0139993 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0141613 | -0.0149884 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0154853 | 0.0984840 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0029118 | -0.0269110 | -0.0139953 | -0.0269110 | -0.0269110 | 0.0000049 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0986229 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0188739 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0082249 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0208911 | -0.0269110 | 0.0301738 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0042623 | -0.0269110 | -0.0269110 | -0.0139595 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0088945 | -0.0147459 | 0.2049075 | -0.0074738 | -0.0269110 | -0.0021788 | -0.0269110 | 0.0476872 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0221739 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0264160 | -0.0269110 | -0.0269110 | -0.0156665 | -0.0269110 | -0.0269110 | 0.0453802 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0090432 | -0.0269110 | -0.0153160 | -0.0269110 | -0.0162067 | 0.0187765 | -0.0269110 | -0.0139446 | -0.0269110 | 0.1642988 | -0.0269110 | 0.1804709 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0019228 | 0.1059460 | -0.0269110 | -0.0269110 | -0.0221825 | 0.0805549 | -0.0269110 | -0.0269110 | 0.0255417 | -0.0152415 | 0.0981544 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0253015 | -0.0269110 | -0.0269110 | -0.0037036 | -0.0010221 | -0.0269110 | 0.0020690 | -0.0269110 | 0.0221871 | 0.1065170 | -0.0269110 | 0.0239604 | -0.0269110 | -0.0162900 | -0.0055260 | -0.0269110 | -0.0086490 | 0.0318725 | -0.0269110 | 0.0087245 | -0.0220093 | -0.0269110 | -0.0167094 | -0.0013990 | -0.0269110 | -0.0269110 | 0.0020126 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0019510 | -0.0269110 | 0.0026092 | -0.0009221 | -0.0065497 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0228068 | -0.0269110 | -0.0269110 | 0.3891858 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0128875 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0177987 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0020044 | 0.0099650 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0213027 | 0.0069909 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0042328 | -0.0269110 | 0.0021834 | -0.0084009 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0261882 | 0.0043082 | -0.0269110 | -0.0269110 | -0.0026469 | -0.0269110 | -0.0269110 | 0.0192486 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0081910 | -0.0269110 | -0.0269110 | -0.0092049 | 0.0605828 | 0.1071930 | -0.0269110 | -0.0269110 | -0.0094384 | 0.0995109 | -0.0269110 | -0.0269110 | -0.0110433 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0208673 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0092883 | -0.0240476 | 0.0632175 | -0.0269110 | -0.0269110 | 0.0263989 | -0.0269110 | -0.0269110 | -0.0036621 | -0.0269110 | 0.0189855 | 0.0312402 | 0.0056268 | -0.0014349 | 0.0352123 | -0.0269110 | 0.0142313 | -0.0112907 | -0.0269110 | -0.0269110 | 0.0204305 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1499716 | -0.0351565 | -0.0269110 | -0.0269110 | -0.0134438 | 0.0260584 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0002700 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0029226 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0969467 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0253542 | -0.0269110 | -0.0147706 | -0.0269110 | 0.0001138 | -0.0015919 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0056947 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0212153 | 0.0244652 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0200666 | -0.0269110 | 0.0073634 | -0.0009532 | -0.0172264 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0272339 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0061569 | -0.0269110 | -0.0269110 | -0.0204268 | -0.0269110 | -0.0082195 | -0.0269110 | -0.0767476 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0018893 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0826441 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0461663 | -0.0193258 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0238405 | -0.0269110 | -0.0269110 | 0.0315878 | -0.0269110 | 0.0078278 | -0.0269110 | -0.0002747 | -0.0269110 | -0.0150303 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0075425 | -0.0269110 | -0.0269110 | -0.0014279 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0541633 | -0.0184892 | 0.0000322 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0029207 | -0.0269110 | -0.0269110 | 0.0292624 | -0.0269110 | -0.0269110 | -0.0064013 | -0.0269110 | 0.0984362 | -0.0269110 | 0.0095425 | -0.0134675 | -0.0174286 | -0.0269110 | -0.0269110 | -0.0108267 | -0.0269110 | 0.0090762 | 0.0365311 | -0.0102633 | -0.0269110 | -0.0251861 | -0.0269110 | 0.0114723 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0426291 | -0.0269110 | -0.0269110 | -0.0027003 | -0.0269110 | -0.0269110 | -0.0196378 | -0.0177710 | 0.0145962 | -0.0269110 | 0.0262060 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0057029 | -0.0269110 | -0.0055360 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0063692 | -0.0269110 | -0.0269110 | 0.0203624 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | 0.0001217 | -0.0262352 | -0.0269110 | -0.0122039 | -0.0269110 | -0.0106364 | -0.0166226 | -0.0269110 | 0.0541633 | 0.0541633 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001141 | 0.0001148 | 0.0168309 | -0.0269110 | -0.0186951 | -0.0269110 | 0.0444249 | -0.0269110 | -0.0037175 | -0.0226308 | 0.0043550 | 0.0006572 | -0.0269110 | -0.0269110 | -0.0040840 | 0.0055544 | 0.0018076 | 0.0232064 | -0.0269110 | -0.0269110 | 0.0027644 | -0.0269110 | 0.0001138 | -0.0269110 | 0.0103838 | 0.0165859 | 0.0204723 | 0.0174830 | 0.0103682 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0071942 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1364619 | -0.0269110 | 0.0246805 | 0.0158579 | -0.0269110 | -0.0269110 | -0.0103573 | -0.0269110 | -0.0234272 | 0.0529754 | -0.0090961 | -0.0269110 | 0.0996936 | -0.0269110 | 0.3125838 | 0.0025625 | -0.0269110 | -0.0269110 | 0.0005773 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1055361 | 0.0780103 | 0.0353354 | -0.0269110 | -0.0269110 | -0.0075058 | -0.0269110 | -0.0093847 | -0.0269110 | -0.0269110 | -0.0094565 | 0.0016309 | -0.0099404 | -0.0084437 | -0.0269110 | -0.0269110 | 0.0304348 | -0.0078450 | 0.0048337 | -0.0269110 | 0.1136699 | 0.1146876 | 0.0839309 | -0.0269110 | -0.0269110 | -0.0018874 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0169396 | -0.0254895 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0994926 | -0.0269110 | -0.0269110 | -0.0268809 | 0.0068070 | -0.0249035 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0162608 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0311248 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0006712 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0097714 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0972226 | -0.0261518 | 0.0020138 | -0.0269110 | -0.0252312 | 0.1554946 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0246562 | -0.0120787 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0404066 | -0.0186451 | 0.1936173 | 0.0240781 | -0.0097936 | -0.0183778 | -0.0269110 | -0.0040633 | -0.0262875 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0000791 | -0.0269110 | -0.0269110 | 0.0288537 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0079217 | 0.0933244 | -0.0269110 | 0.0058730 | 0.0091220 | -0.0255244 | 0.0167601 | -0.0053144 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0251066 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1082127 | -0.0250846 | -0.0254200 | 0.0020091 | -0.0269110 | -0.0269110 | -0.0089602 | -0.0269110 | -0.0266611 | -0.0269110 | -0.0269110 | 0.0976258 | 0.0086413 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0100164 | -0.0269110 | 0.0225959 | -0.0156800 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0013286 | -0.0269110 | -0.0223446 | 0.0252082 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0014715 | 0.1158656 | -0.0269110 | -0.0205464 | 0.0545732 | -0.0269110 | -0.0269110 | 0.0602307 | -0.0269110 | -0.0269110 | 0.0375964 | -0.0269110 | -0.0269110 | 0.0043334 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0012425 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0242632 | -0.0269110 | -0.0243791 | -0.0143227 | -0.0269110 | 0.0283641 | 0.0034564 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1017030 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0015821 | 0.0173793 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0455784 | -0.0269110 | -0.0269110 | 0.0108235 | -0.0269110 | 0.1645959 | -0.0013850 | -0.0269110 | 0.0158454 | -0.0269110 | 0.0356780 | -0.0269110 | 0.0573741 | -0.0269110 | -0.0238306 | 0.0194399 | -0.0269110 | -0.0206248 | 0.0199208 | 0.0052968 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0240780 | -0.0269110 | -0.0269110 | -0.0136514 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0190509 | -0.0269110 | -0.0269110 | 0.3828822 | -0.0040653 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0259892 | 0.0079891 | -0.0096491 | 0.0035768 | -0.0269110 | 0.0207903 | -0.0269110 | 0.0454152 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0077893 | -0.0269110 | -0.0021023 | -0.0269110 | -0.0269110 | -0.0134197 | -0.0269110 | -0.0269110 | 0.0492560 | 0.0245288 | 0.0044729 | -0.0175276 | -0.0067831 | -0.0213587 | -0.0269110 | -0.0062450 | -0.0269110 | -0.0149369 | -0.0269110 | 0.0215950 | -0.0269110 | -0.0269110 | -0.0161260 | -0.0040788 | -0.0269110 | 0.0217336 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0083954 | -0.0269110 | 0.0101311 | -0.0269110 | -0.0003274 | -0.0269110 | -0.0269110 | -0.0082412 | -0.0269110 | 0.0090531 | -0.0269110 | -0.0009501 | -0.0216114 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0190964 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0063505 | -0.0269110 | -0.0017419 | -0.0269110 | -0.0269110 | -0.0039162 | 0.0116316 | -0.0269110 | -0.0106327 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0197517 | -0.0269110 | -0.0114584 | -0.0269110 | -0.0269110 | 0.0794691 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0189131 | -0.0269110 | 0.0272588 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0366992 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0640731 | -0.0269110 | -0.0015626 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0068270 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0049520 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.2179496 | -0.0269110 | -0.0269110 | 0.0380607 | -0.0269110 | -0.0269110 | -0.0149552 | -0.0269110 | -0.0269110 | 0.0008912 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0091898 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0175147 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0051197 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0098590 | -0.0269110 | 0.0541158 | 0.0304422 | -0.0269110 | -0.0120523 | -0.0208143 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0063850 | -0.0269110 | 0.0200494 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0444820 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0225053 | -0.0269110 | 0.0371346 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0214769 | -0.0269110 | 0.0019171 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0015969 | -0.0269110 | -0.0147498 | 0.0119363 | -0.0269110 | -0.0143847 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0233240 | -0.0199217 | -0.0269110 | -0.0163500 | -0.0269110 | -0.0249595 | 0.0181455 | -0.0269110 | -0.0139226 | -0.0239064 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | 0.1073411 | -0.0269110 | -0.0269110 | -0.0209061 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0170874 | -0.0269110 | 0.2042825 | 0.0047443 | -0.0269110 | -0.0269110 | -0.0013420 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0219755 | -0.0138251 | -0.0067703 | 0.0178618 | -0.0022331 | -0.0073161 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0234498 | -0.0105796 | -0.0269110 | 0.0020984 | -0.0089592 | -0.0269110 | -0.0269110 | -0.0096787 | -0.0231836 | 0.0274774 | -0.0269110 | 0.0174240 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0166647 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0240979 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0352865 | -0.0269110 | 0.5237352 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0029984 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0048396 | -0.0269110 | 0.0048551 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0214345 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0259556 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0076293 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0065479 | -0.0269110 | -0.0269110 | 0.0222372 | -0.0164843 | 0.0446378 | 0.0389058 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0258857 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0016092 | -0.0255201 | -0.0262783 | 0.0246317 | -0.0269110 | 0.0769948 | -0.0037558 | -0.0269110 | -0.0219310 | -0.0269110 | -0.0244493 | 0.0386726 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0201032 | -0.0269110 | -0.0269110 | -0.0200301 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0195428 | -0.0044388 | -0.0269110 | 0.0404731 | -0.0269110 | -0.0260319 | -0.0269110 | -0.0282230 | -0.0269110 | -0.0160193 | -0.0269110 | 0.0259972 | -0.0148010 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0124725 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0217312 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0013188 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0174508 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0084102 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0195882 | -0.0269110 | -0.0269110 | -0.0205803 | 0.0226328 | -0.0008481 | -0.0269110 | 0.0473024 | -0.0269110 | -0.0030129 | -0.0160039 | -0.0269110 | -0.0269110 | 0.0099336 | -0.0269110 | 0.0133287 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0474536 | -0.0217687 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0072280 | -0.0255388 | 0.0489234 | 0.0210119 | -0.0003488 | -0.0131651 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0842618 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0201827 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0020552 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0270077 | -0.0077244 | -0.0167404 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0195142 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0044937 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0010041 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0439232 | -0.0269110 | -0.0269110 | -0.0269110 | 0.2861869 | -0.0092033 | -0.0269110 | -0.0269110 | -0.0269110 | 0.4380416 | -0.0269110 | -0.0269110 | -0.0253774 | -0.0269110 | -0.0269110 | 0.0062466 | -0.0269110 | -0.0231214 | -0.0000712 | -0.0269110 | 0.0097420 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0052541 | 0.0461860 | -0.0269110 | 0.0372083 | 0.0259255 | -0.0269110 | -0.0259509 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0494407 | 0.0111397 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0258351 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0108181 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0155088 | -0.0269110 | 0.0726933 | -0.0269110 | 0.0542735 | 0.0117352 | 0.0318716 | -0.0079546 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0984522 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0064612 | -0.0269110 | 0.0245974 | -0.0269110 | -0.0269110 | -0.0105862 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0054692 | -0.0269110 | -0.0269110 | -0.0168770 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0391116 | -0.0298908 | -0.0269110 | 0.0042920 | -0.0100978 | 0.0683456 | -0.0269110 | 0.0001138 | 0.0016796 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0066641 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0018363 | 0.0077484 | -0.0269110 | -0.0269110 | 0.0073049 | -0.0269110 | -0.0110028 | -0.0269110 | -0.0269110 | -0.0136467 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0082060 | -0.0252530 | 0.0386568 | -0.0269110 | -0.0269110 | -0.0047905 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0263072 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0032292 | 0.0001138 | 0.0197044 | 0.0510652 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1011743 | -0.0269110 | -0.0269110 | 0.0184188 | 0.0057480 | 0.0001138 | -0.0060337 | 0.0178346 | 0.0334671 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0260539 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1338290 | 0.0009201 | -0.0047441 | -0.0269110 | -0.0269110 | 0.0893064 | -0.0269110 | -0.0269110 | -0.0174606 | 0.0059569 | 0.0016242 | -0.0269110 | 0.2225713 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0116999 | -0.0269110 | 0.0049313 | -0.0134747 | -0.0269110 | -0.0269110 | -0.0251514 | 0.0046496 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0064427 | -0.0269110 | 0.0095335 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0128320 | -0.0269110 | 0.0159750 | -0.0269110 | -0.0269110 | -0.0160530 | -0.0269110 | -0.0269110 | 0.0056410 | -0.0070499 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0145503 | 0.0036981 | -0.0269110 | -0.0269110 | 0.0056266 | -0.0269110 | -0.0269110 | -0.0173167 | -0.0220323 | -0.0037834 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0219499 | -0.0269110 | 0.0094876 | 0.0191963 | -0.0267695 | -0.0269110 | 0.0240523 | -0.0155906 | -0.0269110 | 0.0011687 | -0.0269110 | -0.0269110 | -0.0082296 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0811880 | -0.0269110 | 0.0074513 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0221053 | 0.0791835 | -0.0269110 | -0.0269110 | -0.0159894 | 0.0004519 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0105128 | -0.0269110 | -0.0087429 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0243303 | 0.0094343 | 0.0917219 | -0.0269110 | -0.0269110 | -0.0206348 | 0.0610792 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0226739 | -0.0269110 | -0.0269110 | 0.0148751 | -0.0117144 | -0.0269110 | -0.0254700 | 0.0502263 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0252310 | -0.0021452 | -0.0040087 | -0.0269110 | -0.0089500 | 0.0248911 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0001312 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0151574 | 0.0208719 | -0.0314421 | 0.1569759 | -0.0269110 | -0.0269110 | 0.0397280 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0187803 | -0.0227315 | -0.0269110 | 0.0668834 | -0.0269110 | -0.0146544 | -0.0257690 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0262329 | -0.0269110 | 0.0315182 | -0.0269110 | 0.0858239 | 0.0852040 | 0.0026494 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0315571 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0092314 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0026988 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0117232 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0029332 | -0.0269110 | -0.0269110 | 0.0158796 | -0.0269110 | -0.0269110 | 0.0103138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0197005 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0164284 | -0.0269110 | 0.0020749 | -0.0269110 | 0.0001138 | 0.0001138 | 0.0246212 | -0.0269110 | 0.0074375 | -0.0007282 | -0.0269110 | 0.0657166 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0163867 | 0.0759934 | -0.0269110 | 0.0010010 | 0.0124313 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0109632 | -0.0269110 | -0.0269110 | 0.0979479 | -0.0230896 | -0.0269110 | -0.0012580 | -0.0269110 | -0.0269110 | 0.0066453 | -0.0269110 | -0.0269110 | -0.0131469 | 0.0345996 | -0.0269110 | -0.0243622 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0228912 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0621467 | -0.0269110 | -0.0269110 | 0.0238245 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0084324 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0188890 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0111929 | -0.0269110 | -0.0269110 | 0.0286934 | -0.0130335 | -0.0028971 | -0.0269110 | 0.0038094 | -0.0251683 | -0.0182956 | -0.0202795 | -0.0269110 | -0.0269110 | -0.0122704 | -0.0164414 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0417779 | -0.0230488 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0206871 | -0.0269110 | -0.0269110 | -0.0222379 | -0.0217656 | 0.0363700 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0020341 | -0.0080829 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0079512 | -0.0269110 | -0.0269110 | 0.0042277 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001143 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0029617 | -0.0269110 | -0.0269110 | -0.0077839 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0085021 | -0.0269110 | 0.0277222 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0088795 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0136535 | -0.0269110 | 0.0059459 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0206571 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0020727 | -0.0269110 | -0.0013086 | -0.0269110 | 0.0080192 | -0.0232443 | -0.0151491 | -0.0269110 | -0.0269110 | 0.0364819 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | 0.0148951 | -0.0024412 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0099409 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0023076 | -0.0269110 | -0.0269110 | -0.0000315 | -0.0049652 | -0.0034469 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0150344 | -0.0269110 | -0.0023425 | -0.0269110 | -0.0211804 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0207183 | -0.0269110 | -0.0248813 | 0.0053608 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0126740 | -0.0269110 | 0.0050460 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0214729 | -0.0269110 | 0.0068935 | 0.0355392 | -0.0269110 | -0.0269110 | 0.0136261 | -0.0269110 | -0.0037933 | 0.0111475 | 0.0150507 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0025774 | -0.0005158 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0214699 | 0.0012776 | -0.0269110 | -0.0076790 | -0.0269110 | 0.0063489 | 0.0160287 | -0.0269110 | 0.0195994 | -0.0269110 | 0.0156693 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0067534 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0198342 | -0.0269110 | -0.0239374 | -0.0120291 | -0.0233608 | -0.0269110 | 0.0126573 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0111327 | -0.0269110 | -0.0269110 | 0.0001138 | 0.0046098 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0114906 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0485338 | -0.0269110 | -0.0220131 | -0.0196632 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0015247 | -0.0269110 | -0.0269110 | -0.0207376 | 0.1205270 | 0.0001138 | -0.0269110 | 0.0212146 | 0.0942353 | 0.1160454 | -0.0224949 | -0.0269110 | -0.0269110 | -0.0041925 | -0.0269110 | 0.0016235 | -0.0033082 | -0.0269110 | -0.0269110 | -0.0242192 | -0.0269110 | -0.0269110 | -0.0057630 | 0.0116006 | 0.0132771 | -0.0269110 | -0.0269110 | -0.0257610 | 0.0616286 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0063733 | 0.0119991 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0161456 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0010551 | -0.0269110 | 0.0171391 | -0.0222687 | -0.0269110 | 0.0775197 | 0.0047883 | -0.0075634 | -0.0217781 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | 0.0401942 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0121474 | 0.0071721 | -0.0269110 | -0.0081283 | -0.0269110 | 0.0357593 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0107358 | -0.0207713 | -0.0246606 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0033432 | -0.0269110 | -0.0269110 | -0.0098876 | 0.1373449 | -0.0230829 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0109534 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0628096 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0062296 | -0.0028566 | -0.0269110 | 0.0028624 | 0.0544514 | -0.0269110 | 0.1474077 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0089238 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0572919 | -0.0269110 | 0.0195774 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0018968 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0145221 | 0.1856513 | -0.0157900 | -0.0269110 | -0.0269110 | 0.0406020 | -0.0269110 | 0.0326450 | 0.0688635 | 0.0635425 | -0.0269110 | -0.0269110 | 0.1736058 | 0.0276486 | -0.0269110 | -0.0269110 | 0.0321971 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0213315 | 0.0994936 | -0.0269110 | -0.0269110 | 0.0113756 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0015735 | 0.2654913 | -0.0033692 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0045896 | -0.0269110 | 0.0539996 | 0.0462526 | -0.0269110 | -0.0269110 | -0.0269110 | 0.4744021 | -0.0269110 | -0.0269110 | 0.0208513 | 0.0552768 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0387109 | 0.2219549 | -0.0269110 | -0.0262441 | -0.0269110 | -0.0269110 | -0.0046442 | -0.0177066 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0413463 | -0.0269110 | -0.0269110 | -0.0087670 | -0.0269110 | 0.0198605 | -0.0269110 | 0.2152677 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0176131 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0141098 | -0.0021712 | 0.1629832 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0083158 | -0.0269110 | -0.0269110 | -0.0124358 | 0.0530225 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0032498 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0180102 | -0.0269110 | -0.0269110 | 0.1438093 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0014091 | -0.0204189 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0419400 | -0.0269110 | -0.0202301 | 0.0030975 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0188093 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0509818 | -0.0269110 | 0.0001988 | 0.0057897 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0102708 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0942552 | -0.0269110 | 0.0282380 | -0.0269110 | 0.0788402 | -0.0269110 | -0.0269110 | 0.0164131 | 0.0142478 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0067403 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0206837 | 0.0001138 | -0.0269110 | 0.0061666 | 0.0231145 | 0.0066237 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0007534 | -0.0269110 | -0.0234887 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0208195 | 0.0114992 | -0.0032957 | -0.0269110 | -0.0269110 | 0.0090350 | 0.0164712 | 0.0583030 | -0.0269110 | -0.0269110 | -0.0158555 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0007052 | -0.0070597 | -0.0269110 | -0.0154997 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0051985 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0447460 | -0.0269110 | -0.0145787 | -0.0269110 | 0.0107835 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0541330 | -0.0269110 | -0.0015494 | 0.0293027 | -0.0269110 | -0.0269110 | -0.0250499 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0184657 | -0.0013123 | 0.0443075 | -0.0251821 | 0.0031974 | -0.0082063 | 0.0208771 | -0.0194148 | -0.0087817 | -0.0050021 | 0.0179439 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0125201 | 0.2645255 | -0.0135538 | -0.0097143 | 0.0412610 | -0.0269110 | -0.0269110 | 0.0053511 | 0.0129337 | -0.0269110 | -0.0269110 | -0.0046294 | -0.0269110 | -0.0269110 | -0.0172829 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0343696 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0153029 | 0.0113784 | -0.0040247 | 0.0247833 | 0.0570483 | 0.0443858 | 0.0025769 | 0.0109984 | -0.0090134 | -0.0228321 | -0.0269110 | -0.0245662 | 0.0180088 | 0.0585359 | -0.0269110 | 0.0156129 | 0.0001138 | 0.0133278 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0234473 | -0.0269110 | -0.0269110 | -0.0191261 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | 0.0945417 | -0.0269110 | -0.0249681 | -0.0044290 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0008933 | -0.0269110 | -0.0269110 | 0.0257702 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0117523 | 0.0125159 | -0.0031525 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0000274 | 0.0076633 | -0.0269110 | -0.0269110 | -0.0093790 | 0.0317783 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0068805 | -0.0269110 | -0.0185934 | -0.0152076 | 0.0877970 | -0.0269110 | 0.1651740 | 0.0024893 | -0.0269110 | -0.0269110 | 0.0273420 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1120041 | -0.0002076 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0173113 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0001138 | -0.0130020 | -0.0269110 | -0.0269110 | -0.0205492 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0383588 | 0.0207450 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0013023 | -0.0269110 | -0.0269110 | 0.0398272 | -0.0135622 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0134275 | 0.0102861 | 0.0055884 | -0.0269110 | -0.0239980 | -0.0269110 | 0.0121522 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0115026 | -0.0234527 | -0.0269110 | -0.0269110 | 0.0250795 | -0.0059445 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0480686 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0108920 | 0.0753726 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0049590 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0034844 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0242321 | -0.0269110 | -0.0083897 | -0.0251669 | 0.0549481 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0249164 | -0.0269110 | -0.0169387 | -0.0269110 | -0.0269110 | 0.0915925 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0149452 | -0.0269110 | 0.0021362 | -0.0269110 | -0.0269110 | 0.0683745 | 0.0257463 | 0.0070220 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0177982 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0259959 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0025033 | -0.0269110 | -0.0180850 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0152013 | -0.0269110 | -0.0269110 | -0.0100072 | -0.0100564 | 0.0003594 | -0.0269110 | -0.0162401 | -0.0137894 | -0.0257258 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0293557 | -0.0269110 | 0.0001138 | -0.0269110 | -0.0269110 | -0.0111001 | -0.0058827 | 0.0091220 | -0.0269110 | 0.0138703 | -0.0269110 | -0.0269110 | 0.0224134 | -0.0269110 | -0.0269110 | -0.0197044 | -0.0269110 | -0.0269110 | 0.0105774 | -0.0269110 | -0.0124476 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0104488 | -0.0269110 | -0.0269110 | 0.0157597 | -0.0269110 | 0.0188232 | -0.0269110 | 0.1393066 | -0.0269110 | 0.0300818 | -0.0169438 | -0.0269110 | 0.0017824 | -0.0269110 | -0.0068820 | 0.0608966 | -0.0207670 | -0.0269110 | -0.0264186 | -0.0269110 | -0.0269110 | 0.0080736 | -0.0186821 | -0.0269110 | -0.0216988 | -0.0269110 | -0.0269110 | -0.0166460 | -0.0269110 | -0.0269110 | 0.0270659 | -0.0269110 | -0.0242546 | -0.0269110 | -0.0041752 | -0.0190663 | -0.0269110 | -0.0114443 | 0.0396907 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0057165 | -0.0269110 | -0.0269110 | -0.0127631 | -0.0269110 | 0.0091396 | 0.0009146 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0141174 | -0.0011580 | -0.0187203 | -0.0067408 | -0.0269110 | 0.0152319 | -0.0269110 | -0.0269110 | -0.0097459 | -0.0090041 | -0.0269110 | -0.0269110 | -0.0000694 | -0.0269110 | -0.0269110 | 0.0247051 | 0.0183270 | 0.0481164 | -0.0269110 | -0.0269110 | -0.0102242 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0028476 | -0.0269110 | -0.0269110 | 0.0256663 | -0.0269110 | 0.0100120 | -0.0150989 | -0.0269110 | -0.0045394 | 0.0202368 | -0.0269110 | -0.0269110 | 0.0256157 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1818486 | 0.0449752 | 0.0018802 | -0.0131306 | 0.0107333 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0262481 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0229387 | -0.0004376 | -0.0192114 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0174078 | 0.0012659 | -0.0269110 | -0.0269110 | -0.1122433 | 0.0118060 | -0.0269110 | -0.0000894 | 0.0045731 | 0.0344424 | 0.0439515 | -0.0269110 | -0.0269110 | -0.0270973 | 0.0674654 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0102991 | -0.0269110 | 0.0674715 | -0.0269110 | 0.0012003 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0123692 | -0.0126119 | -0.0269110 | -0.0080297 | 0.1498871 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0022645 | 0.0710088 | -0.0129104 | 0.0015361 | -0.0269110 | -0.0269110 | 0.0235763 | -0.0269110 | 0.0265913 | -0.0223224 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0578437 | -0.0269110 | 0.0228154 | 0.0255541 | 0.0249794 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0028789 | -0.0269110 | -0.0163009 | -0.0189670 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0230257 | 0.0359874 | -0.0269110 | -0.0269110 | -0.0250274 | 0.0017105 | -0.0269110 | -0.0269110 | 0.0495827 | 0.0240229 | -0.0269110 | -0.0269110 | 0.0158786 | 0.1014572 | -0.0269110 | -0.0128714 | 0.0323088 | -0.0269110 | 0.0021284 | -0.0269110 | -0.0269110 | 0.0269514 | -0.0269110 | 0.0025948 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0226722 | -0.0269110 | 0.0288516 | -0.0115361 | -0.0244181 | -0.0269110 | 0.0190524 | 0.0242009 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0086950 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0181987 | -0.0269110 | 0.0345379 | -0.0269110 | 0.0074356 | -0.0269110 | -0.0269110 | -0.0018735 | -0.0269110 | -0.0252480 | 0.0017879 | -0.0269110 | -0.0247094 | 0.0111903 | 0.0223815 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0150735 | -0.0269110 | -0.0157604 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0278443 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0129327 | 0.0070187 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0209417 | -0.0269110 | 0.0678579 | -0.0269110 | -0.0213593 | -0.0269110 | -0.0269110 | -0.0175638 | -0.0021685 | -0.0269110 | -0.0269110 | 0.0348419 | -0.0128982 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0186310 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0010457 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0008304 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0265561 | -0.0241631 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0205939 | -0.0269110 | 0.0254446 | -0.0269110 | -0.0169212 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0239479 | -0.0269110 | -0.0203472 | -0.0269110 | -0.0269110 | -0.0184254 | -0.0269110 | -0.0195649 | -0.0269110 | -0.0199417 | -0.0109916 | 0.0019260 | 0.0288308 | -0.0269110 | -0.0269110 | -0.0160218 | 0.0340738 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0178320 | -0.0269110 | -0.0269110 | 0.0281633 | -0.0139170 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0220265 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0100129 | -0.0269110 | -0.0269110 | 0.0053656 | 0.0170358 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0044529 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0245901 | -0.0214901 | -0.0165351 | -0.0269110 | -0.0269110 | -0.0015591 | -0.0044870 | -0.0269110 | -0.0269110 | 0.0470040 | -0.0269110 | 0.0427089 | -0.0269110 | 0.0076206 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0038558 | -0.0074145 | -0.0269110 | -0.0251340 | 0.0116140 | -0.0269110 | 0.0115686 | -0.0269110 | 0.0136767 | -0.0050617 | -0.0269110 | 0.0853771 | -0.0007054 | -0.0269110 | 0.0227721 | -0.0069797 | -0.0269110 | -0.0147473 | 0.0055270 | -0.0269110 | 0.0023587 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0102025 | -0.0269110 | -0.0056383 | 0.0242175 | -0.0269110 | 0.0021669 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0181733 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0047673 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0202981 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0215272 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0007137 | 0.0143074 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0147698 | -0.0269110 | -0.0016506 | 0.0245877 | -0.0269110 | 0.0177906 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0278220 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0003820 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0103839 | -0.0166863 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0264768 | -0.0061719 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0115620 | -0.0181479 | -0.0167286 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0070369 | -0.0255226 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0921595 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0130074 | -0.0269110 | -0.0269110 | 0.0320867 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0107174 | -0.0269110 | 0.0134601 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0036780 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0201420 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0195856 | -0.0269110 | 0.3054563 | 0.0954234 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0037511 | 0.0176525 | -0.0269110 | -0.0269110 | 0.0984021 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0402867 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0152922 | -0.0269110 | -0.0269110 | 0.0085667 | -0.0187549 | 0.0150268 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0334443 | -0.0269110 | 0.0145740 | 0.0185299 | -0.0070139 | -0.0224380 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.5935177 | 0.0838050 | -0.0269110 | 0.1546548 | 0.0114545 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1827812 | -0.0219177 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0228401 | 0.0000672 | -0.0166722 | -0.0269110 | -0.0176196 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0970650 | -0.0072357 | 0.0989288 | -0.0164014 | -0.0150256 | 0.0484297 | -0.0269110 | -0.0115569 | -0.0269110 | 0.0162609 | -0.0269110 | 0.0077153 | 0.0169032 | -0.0269110 | -0.0269110 | 0.0102593 | -0.0269110 | 0.0239958 | -0.0020521 | -0.0269110 | -0.0269110 | 0.0140034 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0252062 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0080755 | 0.1036974 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0218966 | -0.0269110 | -0.0015137 | -0.0200024 | -0.0269110 | 0.0781643 | 0.0122528 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0032107 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1052681 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0271637 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0224760 | 0.0302545 | -0.0269110 | 0.0060294 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0421598 | 0.0395190 | -0.0269110 | -0.0269110 | -0.0043198 | 0.0156257 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0219241 | -0.0269110 | -0.0269110 | 0.3352736 | -0.0122939 | -0.0269110 | 0.0007763 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0202564 | -0.0105031 | -0.0245759 | -0.0269110 | -0.0269110 | -0.0061740 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0826750 | -0.0269110 | -0.0101547 | -0.0269110 | 0.0283437 | -0.0269110 | -0.0269110 | 0.1949725 | -0.0269110 | -0.0269110 | -0.0196777 | 0.0236893 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0155703 | -0.0247515 | -0.0269110 | -0.0269110 | 0.2885753 | -0.0269110 | 0.0255695 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0090919 | -0.0269110 | -0.0269110 | 0.1705454 | -0.0239704 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0252560 | 0.0047155 | 0.1341994 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.1353733 | -0.0269110 | 0.0424847 | -0.0250883 | -0.0269110 | -0.0113800 | -0.0269110 | 0.0541633 | -0.0269110 | 0.0046434 | 0.0361042 | 0.0321015 | -0.0239138 | 0.0112525 | -0.0269110 | 0.0149505 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.2563821 | -0.0054762 | -0.0129232 | 0.0993044 | -0.0187594 | -0.0154574 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0956849 | -0.0269110 | 0.0944153 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0663743 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0145357 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0315467 | 0.0448026 | -0.0196746 | -0.0269110 | -0.0269110 | 0.0848695 | 0.0165041 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0247816 | -0.0269110 | -0.0269110 | 0.0251247 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0135182 | 0.2955326 | -0.0269110 | -0.0269110 | -0.0194531 | 0.0064099 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0320872 | -0.0269110 | -0.0022245 | 0.0492224 | 0.0260835 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.2308412 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0062626 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0643230 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0162680 | -0.0084523 | 0.0242235 | -0.0103277 | -0.0269110 | -0.0269110 | 0.0316985 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0032122 | -0.0269110 | 0.0229645 | -0.0001025 | -0.0269110 | 0.0160701 | -0.0269110 | 0.0154415 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0148288 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0062541 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0325435 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | -0.0269110 | 0.0247990 | -0.0269110 | -0.0269110 | -0.0004579 | -0.0020419 | -0.0269110 | -0.0045121 | -0.0269110 | -0.0084575 | -0.0269110 | 0.0321506 | -0.0269110 | 0.0078419 | -0.0269110 | 0.0194712 |
| Max_201309 | -0.3637536 | -0.3637536 | -0.1284096 | -0.3637536 | -0.3637536 | 1.1309317 | -0.3637536 | 0.6013264 | -0.3637536 | 3.5187725 | -0.3637536 | 0.3670778 | -0.3637536 | 0.9083879 | 2.1958615 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9474311 | -0.3637536 | -0.0736400 | 1.0693804 | 1.0274650 | 0.1502043 | -0.3637536 | 0.9009113 | 0.7574836 | 0.7802293 | 4.2786239 | -0.1059950 | -0.3637536 | -0.3637536 | 0.5413755 | 0.0858583 | -0.3637536 | 1.4348094 | -0.3637536 | 1.0399516 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0057149 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1708144 | 1.2206171 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.5228484 | 0.1671963 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0887683 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.2513176 | -0.3637536 | 0.5852244 | -0.3637536 | -0.0521171 | -0.3637536 | -0.3637536 | 0.7877518 | -0.0077015 | -0.2721106 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5092855 | -0.3379813 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0237781 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | 1.3000996 | -0.3637536 | -0.2348505 | -0.3637536 | -0.2008806 | -0.3637536 | 0.9212513 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9115665 | -0.3637536 | 1.0550032 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3403183 | -0.3637536 | 2.0335402 | -0.3637536 | -0.3637536 | 1.2790919 | -0.3637536 | -0.1454550 | -0.3637536 | 3.0563733 | 1.9965061 | -0.3637536 | 1.3169100 | 1.6900790 | 1.0478116 | -0.3637536 | -0.3637536 | -0.1905161 | -0.1116733 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1804116 | 1.4158663 | -0.3637536 | -0.2186059 | 0.5245503 | 0.6373138 | -0.3637536 | 0.0360795 | 0.0111913 | 1.6798976 | -2.5845133 | -0.3637536 | 0.9426594 | 0.1083696 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2571089 | 0.4120444 | 0.8537683 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9691656 | -0.0174362 | -0.3637536 | 0.9344803 | -0.3637536 | 0.0030374 | -0.3637536 | 0.4140520 | 2.9734183 | 0.3771415 | 0.3764997 | -0.3637536 | 1.1167529 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0866787 | 0.5182056 | -0.3637536 | -0.1863577 | 0.4614711 | 0.6440931 | 0.2030851 | 0.3731367 | -0.3637536 | 0.5450627 | -0.1840389 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2368125 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5925270 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5375810 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0989673 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8140056 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1194884 | -0.3637536 | -0.3637536 | 0.3544051 | -0.2536195 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0099729 | -0.3637536 | -0.0807764 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3616857 | 0.3422875 | -0.3637536 | 0.7161456 | -0.3637536 | 0.3447805 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | 0.2562720 | -0.3637536 | 4.9086712 | -0.3637536 | 1.1099300 | -0.1830354 | -0.1790615 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4719042 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5831488 | 0.3738573 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1735123 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3023966 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6980590 | -0.3637536 | -0.3637536 | 0.6709650 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1003975 | -0.2904687 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0891873 | 0.4099954 | -0.0323040 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5658942 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0251000 | 0.5232926 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7857079 | -0.3637536 | -0.3637536 | -0.3365055 | -0.3637536 | 0.3487402 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5438472 | -0.3637536 | -0.2993103 | -0.0646193 | 0.3968033 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1011464 | 0.3737134 | -0.3637536 | 0.6103420 | -0.3637536 | 0.1825296 | 0.0237153 | -0.3637536 | 0.0469132 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | 0.8897802 | 0.1447487 | -0.3637536 | 0.4879233 | -0.3637536 | -0.0194497 | -0.3637536 | 1.0747376 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6036219 | 0.5333986 | -0.3637536 | 1.0006864 | -0.3637536 | 1.4547651 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5678114 | 0.0668569 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.8713619 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2455005 | 0.9090867 | -0.3637536 | 0.2276099 | 3.1748323 | -0.3637536 | 0.4389918 | -0.3637536 | -0.1326284 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4207180 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7702515 | 1.2585891 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3283724 | 0.3514026 | -0.3637536 | -0.3637536 | 0.4830243 | 0.4082269 | 0.3845329 | -0.3637536 | -0.3637536 | 2.0360460 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.1343627 | 0.9912859 | 0.4116513 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | 0.0813674 | -0.3637536 | 0.7779383 | -0.3637536 | 0.5291510 | 0.6444765 | -0.3637536 | 0.6062313 | -0.3637536 | -0.3637536 | -0.2158362 | 0.5017231 | 1.8975439 | -0.3637536 | -0.3637536 | 0.9368018 | -0.3637536 | 4.5148550 | 1.1539950 | 1.6153194 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2935893 | -0.3637536 | -0.3225088 | -0.3637536 | -0.0918164 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1640394 | 0.7269925 | -0.3637536 | 0.2707492 | -0.3637536 | 1.1629758 | 0.3800573 | 0.6084684 | -0.3637536 | -0.3637536 | 0.5550776 | 1.0462527 | -0.3637536 | 0.9687022 | 1.2428491 | -0.3637536 | 2.2612577 | -0.3637536 | -0.3637536 | 0.0752707 | -0.2508046 | 2.0404675 | 0.3764997 | 2.5703386 | 0.8629097 | -0.3637536 | -0.3637536 | 1.2232398 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4682178 | 0.2943338 | 1.9239198 | -0.3637536 | -0.3637536 | 0.1780880 | -0.3637536 | 1.0683677 | -0.3637536 | -0.3637536 | 3.0412514 | 0.5781202 | -0.1180959 | 0.6160597 | -0.3637536 | 1.8287581 | -0.3637536 | 1.3722395 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8792330 | 1.2734371 | 0.3764997 | -0.0768803 | -0.3637536 | -0.3637536 | 0.1843720 | 0.1078148 | -0.3637536 | -0.0161808 | -0.3637536 | 7.5212018 | -0.3637536 | -0.3637536 | 0.4154607 | 0.4784370 | 0.8448231 | -0.3637536 | -0.3637536 | -0.2364980 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0895382 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0278186 | -0.1620179 | -0.3637536 | -0.3637536 | 0.0202317 | -0.3637536 | -0.3637536 | 0.0295758 | -0.3637536 | -0.3637536 | 1.3929392 | -0.3637536 | 0.1540987 | -0.3637536 | -0.3637536 | -0.3637536 | -1.9528137 | 0.1691445 | -0.3637536 | -0.3637536 | 0.4327752 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3760740 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2458686 | 2.1940308 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.7054422 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0323719 | -0.3637536 | 0.4141127 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7443707 | -0.3637536 | -0.3637536 | -0.2855111 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1303449 | -0.3162937 | -0.3637536 | -0.3637536 | -0.2997868 | -0.3637536 | -0.0614438 | 1.2407779 | 1.8570061 | -0.3637536 | -0.3637536 | 1.0070178 | 1.8386530 | 0.8685519 | -0.3637536 | 0.0495578 | 0.2977706 | -0.3637536 | -0.3637536 | 1.0683322 | -0.3637536 | -0.3637536 | -0.2951586 | -0.3637536 | -0.3637536 | 7.5772463 | 0.1524523 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1064917 | -0.3637536 | 0.6598494 | -0.0979443 | 0.6530005 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5257791 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1257753 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0094124 | -0.3637536 | 0.4459961 | -0.1908366 | -0.3637536 | -0.3637536 | 6.9345837 | -0.3637536 | 3.1657316 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1949491 | 0.1860085 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0221340 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0138439 | -0.2708559 | -0.3637536 | 18.3650529 | -0.3637536 | -0.3637536 | 4.3200122 | 1.0617543 | 0.7885372 | -0.3637536 | -0.1642032 | -0.3637536 | -0.3637536 | 0.4912589 | 0.6980316 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0919822 | -0.3637536 | -0.0272939 | 2.3117059 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1641181 | 0.0863553 | -0.2388965 | -0.3637536 | -0.3637536 | 2.6721959 | -0.3637536 | 2.3519950 | -0.3637536 | 0.0627437 | -0.3637536 | -0.3637536 | -0.2525213 | 1.2512799 | -0.3637536 | 0.3884836 | 0.6851438 | -0.3637536 | 0.3999997 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2998543 | 1.8647951 | 0.2957819 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3209753 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7768886 | -0.3637536 | -0.3637536 | 0.2374256 | -0.3637536 | 2.8527430 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1606180 | 0.4188444 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0771429 | -0.3637536 | 0.2719417 | 0.8589678 | -0.0459687 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6028802 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5479830 | -0.3637536 | -0.3637536 | 1.6005343 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1754953 | 1.2955455 | -0.3637536 | -0.3637536 | 0.4223894 | -0.3637536 | -0.3637536 | 0.8391579 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2136874 | -0.3791913 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7093679 | -0.0579906 | 1.6033613 | -0.3637536 | -0.3637536 | -0.3301363 | -0.3637536 | -0.3637536 | 1.4014195 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0710982 | -0.3637536 | -0.3637536 | 0.4429330 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0201620 | 0.3765308 | -0.3637536 | -0.0324570 | 0.4587499 | -0.3637536 | 0.5539154 | 5.3403928 | -0.3637536 | -0.2497916 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7692499 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7854814 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0732756 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0746815 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9786224 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1444041 | -0.3637536 | -0.1648217 | -0.1329737 | 1.3111774 | -0.3637536 | -0.3637536 | 2.3144352 | -0.3637536 | 0.2693568 | -0.1853793 | 0.2999402 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2980593 | -0.1530377 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1086647 | 2.9204206 | -0.2536932 | -0.3211904 | 2.0476880 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1647043 | 0.0489599 | -0.2580703 | 3.3185443 | -0.3637536 | 0.0317665 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6495569 | 0.5061365 | -0.3637536 | -0.2612665 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2201087 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0507233 | 1.0127621 | 7.0740592 | -0.2229614 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4142319 | 0.3574886 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6543071 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.9329746 | -0.3637536 | -0.3637536 | -0.3637536 | 3.3216119 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7815440 | -0.3637536 | -0.3637536 | 1.0541201 | 0.9840440 | 1.8129018 | 0.2216234 | -0.0765864 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2258778 | -0.3637536 | -0.2005633 | -0.3637536 | -0.3637536 | 0.0379024 | -0.3637536 | -0.1149355 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1991809 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1084781 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5442085 | -0.3637536 | -0.0476594 | 0.9338933 | -0.0547931 | 8.5650625 | 1.5753205 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1487113 | -0.0974107 | 1.0845386 | -0.3637536 | -0.1229492 | -0.3637536 | 0.0768817 | -0.3637536 | -0.3637536 | -0.1368528 | 2.3671775 | -0.3637536 | 0.3035326 | 0.3682417 | -0.2117805 | 0.8176032 | -0.3637536 | 0.8775526 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -1.1571725 | -0.0535772 | -0.3637536 | -0.3637536 | 6.8894852 | 4.4504426 | 0.1073166 | 1.1434509 | -0.2105482 | -0.3637536 | -0.1444622 | -0.3637536 | -0.3637536 | 4.0375812 | -0.3637536 | -0.2235355 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0901349 | 0.5388298 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.1752676 | -0.3637536 | -0.3637536 | 1.6627052 | -0.3637536 | -0.3637536 | 2.5328218 | 1.8496058 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4498573 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 6.0044133 | -0.3637536 | -0.3637536 | -0.3637536 | 3.8011102 | -0.3637536 | -0.3637536 | 1.9289750 | -0.3637536 | -0.3426903 | 2.4546370 | -0.3637536 | 6.0311623 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0839982 | -0.0115510 | 0.3060303 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1133203 | -0.3637536 | 5.0886623 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1434407 | -0.3637536 | -0.3637536 | 0.5041215 | -0.3637536 | -0.3637536 | 0.3186968 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5294804 | -0.0583889 | -0.5763219 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3598075 | -0.3637536 | -0.3637536 | 0.3479249 | 1.8607888 | -0.3637536 | -0.3637536 | -0.3637536 | 2.3164206 | -0.1732689 | -0.3637536 | -0.3637536 | -0.3637536 | 2.5075540 | -0.3637536 | 0.9752727 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9417452 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4661939 | 3.4934913 | 0.0503518 | -0.3637536 | -0.3193801 | -0.3637536 | 2.0603840 | -0.0611517 | 1.1479938 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0666354 | -0.3637536 | -0.3637536 | -0.1607940 | -0.3637536 | 1.0000164 | -0.3637536 | -0.1481889 | -0.2468360 | -0.3637536 | -0.3393149 | -0.3637536 | -0.3637536 | -0.3637536 | 4.3104851 | -0.3637536 | 0.2547354 | 0.3356218 | 1.2907857 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.1590731 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2879684 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5570533 | 1.5613860 | -0.3637536 | -0.3637536 | 0.0968055 | -0.2204787 | -0.3637536 | -0.3637536 | -0.0925274 | -0.3546609 | 1.1616544 | 0.1436550 | -0.3637536 | -0.3637536 | 0.7184915 | -0.2864155 | -0.3637536 | -0.3637536 | -0.3637536 | 1.2799935 | 3.6326175 | -0.3637536 | -0.3637536 | -0.2218303 | -0.3637536 | -0.2031181 | 0.2133590 | -0.3637536 | -0.3637536 | -0.2901965 | -0.3637536 | -0.3637536 | -0.2077508 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1904535 | -0.3637536 | 2.6873348 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4264038 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1138608 | -0.3637536 | -0.3637536 | 5.4046586 | -0.2220055 | -0.3637536 | -0.3448644 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2570916 | -0.3637536 | -0.0900277 | -0.3637536 | -0.3637536 | 1.6752436 | -0.3637536 | -0.3637536 | 0.8851847 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3352936 | -0.3637536 | -2.5845133 | 0.9418473 | -0.3637536 | -0.3637536 | 0.2008836 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1289930 | -0.3637536 | -0.0455482 | -0.3637536 | 0.8108381 | 2.1297717 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2088927 | -0.3637536 | 0.1164969 | -0.1030128 | 0.8854282 | 1.1361098 | 0.3001393 | -0.3637536 | -0.3637536 | -0.1762164 | -0.3637536 | -0.3069973 | -0.3637536 | 0.1858067 | -0.2019741 | 1.2765787 | -0.3637536 | -0.3637536 | 3.2747347 | -0.3637536 | -0.3637536 | 0.1041869 | -0.3637536 | 5.1560002 | -0.3637536 | 0.7139063 | 4.3195044 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4284832 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0516113 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4781853 | -0.3637536 | 0.2187216 | -0.3637536 | -0.3637536 | 1.7380030 | -0.3637536 | 1.6388454 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0134609 | 0.7092901 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3371589 | 1.6306345 | 0.5448073 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0503196 | -0.0099707 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.9821296 | 0.3377211 | -0.3637536 | 0.6386677 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1480883 | 1.8222290 | 0.0292896 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3494849 | -0.3637536 | 0.1077471 | -0.3637536 | -0.3637536 | 0.4109895 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.9942224 | -0.3637536 | 0.2245463 | 9.5916160 | 2.2096346 | -0.1585494 | 0.7308115 | -0.3637536 | -0.3637536 | 10.1950334 | -0.3637536 | -0.2104171 | -0.3637536 | 0.3137029 | 1.2016562 | 0.0167040 | 0.2194845 | 0.9190942 | -0.3637536 | 0.8907765 | 3.0643377 | -0.3637536 | 0.9059295 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.8047768 | -0.3637536 | -0.3637536 | 1.1118842 | -0.3637536 | -0.3637536 | 2.4647377 | -0.3637536 | -0.3637536 | 0.4833167 | 2.0486451 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0291661 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3559126 | -0.3637536 | 0.6411928 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1577162 | -0.3548792 | -0.3637536 | 1.0758250 | 0.3103475 | -0.3637536 | -0.1646671 | 0.4822123 | 0.0476363 | 0.9312136 | -0.0000808 | 0.0804276 | 1.1683545 | -0.3637536 | 0.6388765 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7909674 | -0.3637536 | -0.3637536 | -0.3119462 | 3.1263620 | -0.3637536 | -0.3637536 | 2.3991846 | 0.2333224 | -0.3637536 | 1.9101630 | -0.2554986 | -0.3637536 | -0.3637536 | -0.3637536 | 4.0707223 | 0.1785976 | -0.3637536 | -0.3637536 | 0.4139883 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2294879 | 2.8964253 | -0.3637536 | -0.3637536 | 0.7010526 | -0.3637536 | 0.4285121 | -0.3637536 | 0.7717623 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1386318 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3347893 | -0.3637536 | 0.9939619 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2089527 | -0.0781340 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2995529 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2981637 | -0.2710237 | 0.1976310 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8243395 | -0.3637536 | -0.3637536 | 0.5846818 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1793362 | 0.5351530 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.9487737 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1615203 | 2.8025834 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1982057 | 0.4990767 | -0.3637536 | -0.3637536 | 0.4117009 | 0.4667151 | 0.3569139 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9482912 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0971975 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0957092 | 0.4428308 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.7892765 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.2435455 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | 0.2605491 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.7715920 | 1.3953864 | -0.3637536 | 0.1988225 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0245580 | 1.1590510 | -0.3637536 | -0.3637536 | 0.6200015 | 0.4554366 | 0.1065754 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1461894 | 0.7603239 | 1.5124975 | 0.5839749 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3277429 | -0.3355287 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3911100 | 0.5010562 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3813046 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1733594 | 0.3764997 | -0.3637536 | 1.3935143 | -0.3637536 | -0.3637536 | 1.8256320 | -0.3637536 | 0.4819436 | 0.1599986 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4126388 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1758613 | 0.3091836 | 1.1959215 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1022876 | -0.3637536 | 0.0224185 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3271494 | -0.2601010 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9064536 | -0.3637536 | -0.3637536 | 0.0524822 | -0.3637536 | -0.1740673 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3144976 | -0.3637536 | -0.2860360 | -0.3637536 | 0.9421249 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1730129 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1012753 | 0.0696834 | 0.1213123 | -0.2812471 | -0.0071920 | -0.3637536 | -0.3637536 | 0.2068591 | 0.0551543 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.5400978 | -0.3637536 | 0.6006602 | 0.7495036 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4466638 | 0.5264446 | -0.2532197 | -0.3637536 | -0.3637536 | 3.3249579 | 0.6461399 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1725448 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3602829 | 0.8800014 | -0.3637536 | 0.8982997 | -0.3637536 | -0.3637536 | -0.3637536 | 3.2896804 | 0.0431032 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0144573 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0025742 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2836947 | -0.3637536 | -0.3637536 | 0.4921642 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.0569210 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -2.5845133 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3765278 | 0.8344107 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0149017 | -0.3637536 | 0.4075503 | -0.3637536 | 0.1981136 | 0.7370059 | -0.3637536 | -0.3637536 | 0.8533567 | -0.3637536 | -0.3637536 | 0.1181188 | 0.7875156 | 0.3764997 | 1.1189544 | -0.1522874 | 0.3764997 | -0.3637536 | -0.8745375 | -0.3637536 | -0.3637536 | 0.4009532 | 0.1750003 | -0.3637536 | -0.3637536 | -0.2505526 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2403168 | -0.3637536 | 1.5040297 | -0.3637536 | -0.2336682 | 4.0888311 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 10.8985035 | 0.1575927 | -0.3637536 | 3.3804288 | -0.3637536 | 0.9052522 | 1.8063388 | 0.8402017 | 0.5480548 | -0.3637536 | 0.5466047 | 2.5685701 | -0.3637536 | -0.3391882 | -0.2489692 | 0.3040503 | -0.3637536 | 0.4392805 | -0.1771444 | -0.3637536 | -0.3637536 | 0.3618116 | -0.3637536 | -0.1902090 | 1.9099224 | -0.3637536 | 0.1599021 | -0.3637536 | 1.0020832 | -0.3637536 | -0.2522902 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0465073 | 1.4630722 | 0.2492896 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1423560 | 0.6723633 | -0.3637536 | -0.3021367 | 0.9704411 | -0.3637536 | -0.3118616 | -0.3637536 | -0.3623453 | -0.3637536 | 0.2414799 | -0.0158836 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0638281 | -0.3637536 | 0.8762113 | 0.6975149 | -0.3637536 | -0.3637536 | 0.5161070 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3206216 | -0.3637536 | 0.7466263 | -0.3637536 | 0.9380935 | 0.5592504 | -0.3637536 | 1.1679681 | -0.3637536 | 0.1231579 | -0.3637536 | 0.7738720 | -0.3637536 | 6.3298589 | 1.5602845 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6155696 | -0.3637536 | -0.3411172 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0208048 | -0.1153438 | -0.3295429 | -0.5436504 | 0.6491416 | -0.3637536 | -0.3637536 | 3.8677456 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8446595 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5666833 | -0.3637536 | -0.3208866 | -0.3637536 | -0.3637536 | 0.7364907 | 0.8623160 | -0.2028290 | -0.3637536 | 0.4665641 | 2.6616577 | 0.0683660 | 3.0674290 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3150040 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9810941 | 0.1058151 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2501614 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0400432 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3631317 | -0.3637536 | 0.6937507 | -0.3637536 | 0.3487402 | -0.3637536 | -0.3637536 | 0.9534071 | -0.3637536 | -0.3637536 | 1.0638773 | 0.3476436 | -0.3637536 | 0.0768109 | -0.3637536 | -0.3637536 | -0.1232531 | -0.3637536 | -0.0047117 | -0.3637536 | 0.9967838 | 0.3886346 | -0.3637536 | 1.6260686 | -0.1424299 | 3.1153744 | -0.3637536 | -0.0517384 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3802949 | -0.2480890 | -0.3637536 | -0.3637536 | -0.2922845 | -0.3637536 | -0.3637536 | -0.3637536 | 3.0339222 | -0.1812937 | 0.2083601 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6829608 | -0.3637536 | -0.3637536 | 0.4704274 | 1.3080454 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1351859 | -0.3637536 | -0.3637536 | 0.8461156 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2275813 | 2.0124800 | -0.2662986 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8488826 | 0.5687738 | -0.1927380 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.9359534 | -0.3637536 | -0.2665331 | -0.3637536 | -0.3637536 | 0.0096050 | -0.3344708 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2230691 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1714811 | -0.3637536 | -0.3637536 | -0.0089871 | 1.7068317 | 0.0917869 | 0.3764997 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.6531966 | -0.3637536 | -0.3637536 | -0.2614126 | 0.1827181 | -0.3637536 | 0.3157968 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3427787 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1815155 | 0.6749846 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4873163 | 1.3764108 | -0.3637536 | -0.3637536 | 0.5820687 | -0.3637536 | -0.3637536 | 0.4804090 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0096168 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.1333907 | -0.3637536 | -0.3637536 | 0.3644153 | -0.3251526 | -0.3637536 | -0.3637536 | -0.2471904 | -0.3637536 | -0.3637536 | 0.3689063 | -0.3637536 | -0.3637536 | 1.0660307 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2304017 | 0.1297486 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1990505 | -0.3637536 | -0.2971238 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1746690 | 2.1805419 | 1.2422591 | 0.0284539 | 0.8887897 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2447673 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.0210699 | -0.0726729 | -0.3637536 | 0.7390564 | -0.3637536 | -0.2074033 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4828726 | -0.3637536 | 0.3694895 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0936311 | 1.0384245 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2158431 | -0.3637536 | 0.9765837 | -0.3637536 | -0.1036051 | -0.3637536 | 1.8570061 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3650923 | 1.7215494 | -0.1611956 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1642427 | -0.3637536 | -0.3637536 | -0.3534783 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6491490 | -0.3637536 | -0.3637536 | 0.3837201 | -0.3637536 | -0.3637536 | 0.2543264 | -0.3637536 | -0.3637536 | -0.2509727 | 1.5226064 | 0.1885597 | -0.3637536 | -0.2768070 | 1.9405311 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0324803 | -0.3637536 | -0.3224458 | -0.3637536 | -0.3637536 | -0.3637536 | 3.2807115 | 0.9828529 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1928980 | 0.0432508 | -0.3637536 | -0.3637536 | -0.0383676 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2478189 | -0.1510474 | -0.3637536 | 0.1302435 | -0.2806858 | 3.2409288 | 0.1093694 | 0.5838979 | 0.6798799 | -0.3637536 | 3.6551197 | -0.3637536 | 0.2923254 | -0.3637536 | -0.3637536 | 0.1026023 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2508645 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2153874 | -0.3637536 | 0.5922361 | -0.3637536 | -0.0306396 | 0.2035847 | 0.3515337 | -0.3637536 | -0.3637536 | 0.4734373 | 1.5830125 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3406417 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2533322 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3408505 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0357760 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4248153 | 0.6044429 | -0.3637536 | -0.0974898 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0473274 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0600302 | -0.3637536 | -0.3637536 | 3.5173408 | -0.3637536 | -0.3008029 | -0.3637536 | -0.0430920 | 0.1620581 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1651561 | 0.5077939 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1910506 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1053239 | -0.3637536 | 0.2043068 | -0.3637536 | 0.3401604 | -0.3637536 | -0.3637536 | 0.1060803 | -0.3637536 | -0.2207677 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5502645 | -0.3637536 | -0.3637536 | 0.3988598 | -0.3637536 | -0.1731059 | -0.3637536 | -0.3637536 | 1.5397551 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2532678 | 0.6232505 | 0.4830288 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3111478 | -0.3637536 | 1.9060923 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.9474288 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7927907 | 0.0862724 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1300006 | 1.5122717 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7657107 | -0.3637536 | -0.3637536 | 0.4638370 | 0.3454234 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4459310 | -0.3637536 | 0.2458667 | 0.0126464 | 0.5652894 | -0.3637536 | 0.8265292 | 0.3035326 | -0.3637536 | 1.4544712 | -0.3637536 | -0.3147057 | -0.3637536 | 1.1277471 | -0.3637536 | 2.5798553 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1361428 | -0.3637536 | 0.1503083 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6529250 | 0.0630858 | -0.3637536 | -0.3637536 | -0.1618855 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0506050 | -0.3637536 | 0.5246332 | -0.3637536 | 0.2011404 | 1.0341910 | -0.2059482 | 0.6771950 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4737756 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9845651 | -0.1505164 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0567984 | -0.3637536 | 0.0070985 | -0.1346928 | -0.3637536 | -0.3637536 | 0.0081910 | 0.1131144 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4568875 | -0.3637536 | -0.3637536 | 0.4050372 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0824599 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5491423 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1731897 | 0.9515558 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1494041 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1753952 | 2.4065131 | -0.3637536 | 0.5708332 | -0.3637536 | 0.7402305 | -0.3637536 | -0.3637536 | 1.8272642 | -0.3637536 | -0.1809924 | -0.0676364 | 0.2297822 | -0.0913107 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3577751 | -0.3637536 | 0.5508767 | 0.1738090 | 1.6594007 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0985527 | -0.3637536 | -0.3637536 | 0.6783187 | 0.1193874 | -0.3637536 | 0.5504251 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6544736 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.1901142 | -0.3637536 | 0.5500209 | 1.2289901 | -0.3637536 | 3.4235537 | -0.3637536 | 0.3822381 | 2.3696752 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0931932 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1522358 | -0.2129208 | 3.1188877 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.5835692 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0707634 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2845338 | 4.8394916 | -0.0173530 | 1.7765517 | -0.3637536 | -0.3637536 | -0.3398080 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1463504 | 5.4998456 | -0.3637536 | -0.3637536 | 0.2057992 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.8470231 | 0.4708050 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2430018 | 0.7201385 | 2.1228503 | -0.3637536 | 0.0796358 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5048100 | -0.3637536 | -0.3637536 | -0.3637536 | -1.2778730 | -0.3637536 | -2.1414902 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2375101 | 0.3785524 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2965166 | -0.3637536 | 0.6463723 | -0.1671559 | 0.2961552 | -0.3637536 | 0.3764997 | 0.5562013 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7655249 | -0.3454753 | -0.3637536 | -0.3637536 | -0.1698008 | 0.4299163 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2528598 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5816853 | -0.3637536 | -0.3637536 | -0.2529167 | -0.3637536 | 0.1740257 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2502048 | -0.3637536 | -0.3637536 | 0.9683536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7236858 | -0.3637536 | -0.3637536 | -0.3637536 | 1.9658707 | -0.3637536 | 0.3673607 | 0.8806824 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6339257 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5586382 | -0.3637536 | -0.3637536 | 0.7710561 | 0.6940920 | -0.3637536 | -0.3637536 | -0.3280095 | -0.3637536 | -0.3637536 | 2.0861900 | 0.6205079 | -0.3637536 | -0.3637536 | 1.3842464 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2572748 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5895090 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3454693 | -0.2666085 | 0.0875309 | -0.3637536 | -0.3637536 | -0.2657408 | -0.3637536 | -0.3637536 | 0.1269256 | -0.3637536 | 0.1595706 | -0.3637536 | 0.2970293 | -0.3637536 | -0.0439437 | 0.2993742 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2559043 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2891709 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3267497 | 3.5277170 | -0.0826477 | -0.3637536 | 0.2697501 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4895889 | -0.2633122 | 1.3810307 | -0.3637536 | -0.3278142 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6513586 | -0.2962978 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1514308 | -0.3637536 | 1.3437634 | 1.9508021 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1927577 | -0.3637536 | -0.2803127 | -0.3637536 | -0.0730421 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1322184 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0699991 | 1.5036026 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4047536 | -0.3637536 | -0.3637536 | 1.6523498 | 1.7848499 | 1.7981560 | -0.3637536 | 0.6318056 | 0.8472955 | 0.3556942 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3316173 | -0.2484467 | 0.4819554 | 0.2334876 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7096832 | -0.0069432 | -0.3637536 | 0.0213656 | 0.8758486 | -0.3637536 | -0.3177372 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3223018 | 1.0288545 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0419048 | 0.5677841 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.2408689 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2945606 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3342891 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3679923 | -0.3637536 | -0.2446288 | 0.6044666 | -0.0175254 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0596067 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5820635 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0682749 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2319505 | 0.1185199 | 0.3764997 | -0.3637536 | 0.2837372 | -0.3637536 | -0.3637536 | 0.6467676 | -0.3637536 | -0.3637536 | -0.3637536 | 2.8664635 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4560465 | -0.3637536 | 1.6781469 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6248346 | 1.2880194 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8588627 | 1.4416589 | 1.2192387 | -0.3637536 | -0.1265503 | -0.3637536 | -0.3637536 | 0.1218425 | 0.1312173 | -0.3637536 | 0.0347972 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8240664 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1021076 | -0.1394397 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1710035 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3001436 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9117753 | -0.3637536 | -0.3637536 | -0.1478991 | -0.3637536 | -0.1537041 | -0.3637536 | 0.2388955 | -0.3637536 | 0.4758424 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.7900213 | -0.3637536 | -0.3637536 | -0.3637536 | 5.1986543 | -0.3637536 | 2.3972637 | -0.1215779 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1360815 | -0.3637536 | 0.2405608 | -0.3637536 | -0.3637536 | 0.0382139 | -0.3637536 | 0.2788644 | -0.3637536 | -0.1637403 | -0.3637536 | -0.1697619 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5524460 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3765137 | -0.3637536 | 0.4469703 | 0.1066954 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0628751 | -0.3637536 | -0.3637536 | 0.7372813 | -0.3637536 | -0.1413415 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -1.8602473 | -0.3637536 | -0.3637536 | 0.5497508 | -0.3637536 | 0.1658479 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1256653 | 0.7413934 | -0.3637536 | -0.2161682 | -0.3637536 | -0.3637536 | 2.4701179 | -0.3637536 | -0.3637536 | 0.7642932 | 0.7457617 | -0.3637536 | -0.3637536 | -0.1311812 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3334410 | 0.3065142 | -0.3637536 | -0.3637536 | -0.4455037 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.4736555 | -0.3637536 | -0.1674508 | -0.3637536 | -0.3637536 | 1.0069230 | 0.8889829 | 0.0598651 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1371885 | -0.1005596 | -0.3637536 | -0.3637536 | 0.7234726 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3092180 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0932188 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1129223 | -0.3637536 | 0.2883484 | -0.3637536 | -0.3637536 | 0.3926327 | -0.3637536 | -0.3637536 | 0.3764997 | 0.1914364 | -0.3052675 | 0.0720801 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3361050 | -0.3637536 | 13.8467618 | 0.6084025 | -0.3637536 | 0.2502883 | 0.6898718 | 0.3234571 | 1.0095805 | -0.3637536 | 0.0352161 | -0.3637536 | -0.2147122 | -0.3637536 | -0.3497037 | -0.2041180 | -0.3637536 | -0.3637536 | 0.5411749 | -0.3212130 | -0.3544847 | -0.2374648 | -0.0679772 | -0.3637536 | -0.2439580 | -0.2831811 | -0.3637536 | 0.5983439 | -0.3637536 | -0.3637536 | 1.1546168 | 0.2491950 | -0.3637536 | -0.3637536 | 1.9203733 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8693580 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0319775 | 0.5533195 | -0.3637536 | -0.3637536 | 0.2955748 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.1319769 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3682971 | -0.3637536 | 0.1557224 | -0.3637536 | -0.2372784 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2007185 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | 0.6692365 | -0.3637536 | 2.8321898 | 1.3094038 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 6.8860230 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1959843 | 2.3929820 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0450477 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2237835 | -0.3637536 | 2.7215730 | -0.3637536 | 1.6124117 | -0.3637536 | -0.3637536 | 1.4783696 | -0.3637536 | -0.1632772 | -0.3637536 | 0.4245539 | -0.3637536 | 0.2289673 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.7251239 | -0.3637536 | -0.3637536 | -0.3637536 | 2.0620659 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4812299 | -0.3637536 | -0.3637536 | 6.5028265 | 0.5084557 | 0.5004854 | -0.3637536 | -0.3637536 | -0.3347406 | -0.1945272 | -0.3637536 | 0.6522966 | 0.0300498 | -0.3637536 | 0.1985062 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0808179 | -0.3637536 | -0.3637536 | 3.2690517 | -0.3637536 | 0.1492283 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3094031 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8854208 | -0.3637536 | -0.0541522 | -0.3637536 | 0.2273504 | -0.8518326 | 0.2633979 | 0.9028560 | 1.0046238 | 4.4719440 | -0.3637536 | -0.3254241 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0565436 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1791677 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3864790 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0011806 | -0.3637536 | -0.3637536 | -0.3637536 | 6.2851913 | 0.3231242 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.4546413 | -0.3637536 | 0.3327238 | -0.3637536 | -0.1967131 | 0.5815217 | 0.6131793 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8612626 | -0.3637536 | 3.8334252 | 0.6573591 | 3.5243666 | 3.5349418 | 0.9469403 | 0.2964245 | 0.1253825 | -0.3637536 | -0.3637536 | -0.1660310 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.9584897 | -0.3637536 | 0.2227197 | 2.6355808 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.0725996 | -0.3637536 | 1.8088941 | -0.3637536 | 0.2378337 | 1.0888831 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.2433472 | -0.1012464 | 1.4437879 | 8.3384413 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0306068 | -0.3637536 | -0.3637536 | 0.4454779 | 1.7948819 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4186971 | 1.2988115 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0660501 | -0.3637536 | 5.1206183 | -0.3637536 | 1.3093261 | -0.3637536 | 1.5420846 | -0.3637536 | -0.3638456 | -0.3637536 | -0.0632085 | -0.3637536 | -0.3637536 | 1.1185376 | -0.3772810 | -0.3637536 | -0.3637536 | -0.0134743 | 0.3692142 | 0.0088251 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3473379 | -0.3637536 | 0.4701706 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2883012 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0333264 | -0.1859234 | -0.3637536 | 1.5766256 | -0.3637536 | -0.3637536 | 1.0449343 | 3.4622467 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0621818 | -0.3637536 | 7.9792409 | 0.6325555 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.6573909 | 1.1210686 | -0.3637536 | 6.7877774 | -0.0578930 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2372206 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2729313 | 1.3872851 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0234756 | -0.2441922 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2367897 | -0.3637536 | -0.3637536 | -0.2139910 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5168635 | 0.7511189 | -0.3637536 | 0.4333326 | -0.3637536 | -0.3637536 | 0.4617539 | -0.3637536 | 0.6476019 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4539531 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | 0.5335229 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7302171 | 0.2055194 | -0.3211445 | 0.0275744 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4976539 | -0.3637536 | 0.6493156 | 1.4078486 | 0.3764997 | -0.3637536 | 0.6889428 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6559808 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4064081 | -0.3637536 | 0.4609648 | 1.0594455 | -0.0706080 | -0.3637536 | -0.3637536 | 1.3907821 | 0.1007151 | -0.3637536 | 0.7617097 | -0.3637536 | -0.3637536 | -0.0785120 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.8943001 | -0.3637536 | -0.0360898 | 1.2649227 | -0.2406931 | -0.3637536 | 4.1815723 | -0.0871602 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0288856 | 0.4531484 | -0.3637536 | -0.3637536 | -0.3637536 | 1.8935931 | -0.3414960 | 0.5459014 | -0.3637536 | 1.1058830 | 1.2162133 | -0.3463646 | -0.3637536 | 3.2622681 | 0.2447264 | -0.3637536 | -0.3637536 | 0.8551363 | -0.2258294 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8986935 | -0.0811573 | -0.3637536 | -0.3637536 | 0.3764997 | 0.3658243 | 0.5611840 | -0.3637536 | -0.2664516 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2929739 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2887935 | 1.2770895 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2520649 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3191601 | -0.3637536 | -0.3637536 | -0.1688704 | 1.0792717 | -0.3637536 | -0.1161548 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0355557 | -0.1000814 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.9303681 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 11.1867803 | -0.3637536 | 0.3819368 | -0.3637536 | 3.0679168 | -0.3637536 | -0.3637536 | 0.4554699 | -0.3637536 | -0.3637536 | 0.4396581 | -0.3637536 | -0.3637536 | 0.9966638 | -0.3637536 | 1.0349527 | -0.3637536 | -0.3637536 | 0.0619517 | -4.1688728 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0776823 | -0.3637536 | -0.3637536 | 1.0533428 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1372963 | -0.3637536 | 0.2621816 | 0.1691545 | 1.2208207 | -0.3637536 | 0.6361990 | -0.3637536 | -0.3637536 | -0.3117045 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1129766 | -0.3637536 | -0.0193574 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4938194 | -0.3637536 | 2.8392341 | 0.2236680 | -0.3637536 | 0.7062521 | -0.3637536 | 1.7037211 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7733753 | -0.3637536 | -0.3052690 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0689149 | 0.4628391 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7555308 | -0.1974530 | 2.2441800 | -0.3637536 | -0.3637536 | -0.5765686 | -0.3637536 | -0.3637536 | 1.9245231 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4527583 | -0.3637536 | -0.3637536 | 0.2522200 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0060812 | -0.3637536 | -0.3637536 | -0.3637536 | 1.0473845 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4069988 | 2.1083413 | -0.3637536 | -0.0186615 | 0.3596980 | 0.3700626 | -0.3637536 | 0.1664624 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0286762 | -0.3637536 | -0.3637536 | -0.2539967 | -0.0709595 | -0.3637536 | 1.8073477 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6064386 | 0.0185639 | -0.3637536 | 0.5657269 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1049620 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5081944 | -0.3637536 | -0.2644943 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0882264 | -0.3637536 | -0.3637536 | 1.6827498 | 0.4437953 | -0.0755962 | -0.0714612 | -0.3637536 | -0.3637536 | -0.3637536 | 2.9137576 | -0.3637536 | 1.1017835 | -0.3637536 | 1.1377835 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5022191 | 1.2666631 | -0.3637536 | -0.3637536 | 0.8574355 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6706918 | -0.3637536 | 14.6893551 | -0.3637536 | 0.6433151 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8034896 | -0.3637536 | 0.2624312 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5239374 | -0.3637536 | -0.3637536 | 0.2626145 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3587038 | 1.0013341 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2823073 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2837324 | -0.1383511 | -0.3637536 | -0.3637536 | 0.6098897 | -0.3637536 | 0.3049201 | -0.3637536 | -0.3637536 | -0.0334673 | -0.3637536 | 0.5211385 | -0.3637536 | 0.2590181 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.1819653 | 0.1240637 | 1.1325640 | -0.3637536 | -0.3637536 | 1.7125960 | -0.3637536 | -0.3637536 | 0.2804339 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3805059 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1077433 | -0.3637536 | -0.1379306 | -0.0743567 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8753918 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1093537 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2599103 | -0.2160905 | -0.0757173 | -0.3637536 | 0.6476285 | -0.0401998 | -0.3637536 | 0.7399966 | 0.6048397 | -0.3637536 | -0.2498182 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4710641 | 0.3764997 | -0.3637536 | 0.8276300 | -0.3637536 | 0.3461110 | 0.6668381 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3151003 | -0.3637536 | -0.2630959 | -0.3637536 | 0.6637979 | -0.3637536 | 1.2135417 | -0.3637536 | 0.3613965 | -0.1528494 | 0.3786205 | -0.3637536 | 0.3704786 | -0.3637536 | -0.3637536 | 0.3986799 | -0.3637536 | 0.4541359 | -0.3637536 | -0.3637536 | 0.2677133 | -0.3637536 | -0.3637536 | 1.0159548 | -0.3637536 | -0.3637536 | -0.2034648 | -0.3637536 | -0.3637536 | -0.1958786 | -0.3637536 | -0.3637536 | 1.2296978 | 0.9384577 | 0.6617266 | -0.3637536 | 0.1497724 | 2.3358234 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1432867 | -0.3945364 | -0.2033040 | -0.3637536 | 0.9845059 | 0.0163364 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1573128 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2377413 | -0.3637536 | -0.2222830 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1894199 | -0.0227522 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1765441 | 3.8010828 | -0.3637536 | 1.4004483 | 1.0103282 | -0.3637536 | -0.3637536 | -0.3637536 | 1.7603165 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3250180 | 1.1591383 | -0.3637536 | -0.3637536 | 1.9341746 | -0.3637536 | -0.3637536 | -0.3637536 | 1.7386233 | -0.3637536 | 0.7955578 | -0.3637536 | -0.6983374 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0573899 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4776220 | -0.3637536 | 2.0326882 | -0.3637536 | -0.0767811 | 0.2538445 | 0.2436852 | -0.3637536 | -0.3637536 | 0.6858500 | 2.1291795 | 0.4402791 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3731167 | -0.3637536 | 0.3354268 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9431539 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0753623 | -0.3334726 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5883935 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3200627 | -0.3637536 | -0.3637536 | 2.4360085 | -0.2569022 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4191819 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2725116 | -0.3256832 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3051500 | -0.3637536 | -0.3208606 | 2.2020396 | -0.1530426 | -0.3637536 | -0.3637536 | -0.1552026 | -0.3767781 | 0.1197006 | 1.2406387 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0818281 | 0.5897178 | -0.3637536 | -0.3637536 | -0.3637536 | 1.1068602 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3506374 | -0.3637536 | 1.5292198 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5134761 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1437811 | -0.3637536 | -0.2993627 | 0.8520850 | -0.1185734 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3797687 | 0.7412928 | 0.8134349 | -0.3637536 | -0.3637536 | -0.2037726 | 0.9294289 | 0.4583887 | -0.3637536 | -0.3637536 | 1.6736943 | -0.3637536 | -0.1997786 | -0.3637536 | 0.2472662 | 0.1626921 | -0.3637536 | 0.6426673 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3488488 | 0.9018019 | 0.2630253 | -0.3637536 | -0.3637536 | 0.4853606 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.3118376 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4675101 | -0.3637536 | 0.0503152 | -0.3637536 | -0.3128832 | 2.1482610 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1455155 | -0.3637536 | 0.0488817 | 0.7277728 | 0.6773282 | -0.2652840 | -0.0022421 | 0.4141586 | 0.5433031 | -0.3637536 | 0.1708738 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.0604070 | -0.3637536 | -0.3637536 | 0.3568103 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3128719 | -0.3637536 | 0.2097737 | -0.3637536 | 0.2532646 | 2.2397644 | -0.3637536 | -0.1259723 | 0.9576540 | -0.3637536 | 1.6508908 | 0.3637324 | 0.7026153 | 1.4194639 | 0.4327374 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0677756 | -0.3637536 | 2.9261687 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3764997 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3800914 | -0.3637536 | 1.4680497 | 1.5501763 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1387549 | -0.2408712 | -0.3637536 | -0.2900337 | -0.3637536 | -0.1315046 | -0.2323665 | -0.1560388 | -0.3637536 | 0.4093314 | 0.6855857 | -0.2587890 | 1.4777374 | 1.7234770 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3096907 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1738080 | 0.3006082 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3120176 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1475691 | 0.1039210 | -0.3637536 | -0.2334048 | -0.3637536 | -0.3637536 | 2.8931393 | -0.3637536 | 0.6281058 | -0.3637536 | 1.6910073 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0974914 | 1.3341349 | -0.3637536 | 2.1761900 | -0.3637536 | -0.1241993 | -0.3637536 | 0.4086807 | -0.3637536 | 2.5390222 | -0.3637536 | -0.3637536 | -0.3164957 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1105287 | 1.6930112 | -0.3637536 | -0.3637536 | 0.3489379 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.5457141 | -0.3637536 | -0.3637536 | 0.0038766 | -0.3637536 | -0.3637536 | 1.7394613 | 0.4946648 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9026813 | 0.3678103 | -0.3637536 | -0.2403784 | -0.3637536 | 1.4479363 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.9859137 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0363638 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2293798 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8700021 | -0.3637536 | -0.3637536 | -0.3268230 | 1.9250021 | -0.0806887 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 2.1101468 | -0.3637536 | -0.3637536 | -0.3637536 | 1.3140600 | -0.3637536 | 0.3283919 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.2058585 | 6.1063587 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.8556893 | -0.3268741 | 1.0884663 | -0.3637536 | -0.3637536 | -0.1188048 | -0.3637536 | 12.3968056 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1844149 | -0.3637536 | -0.3637536 | 0.8230700 | -0.3637536 | 1.1540306 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2466739 | -0.3319002 | 0.6558809 | -0.3637536 | -0.3637536 | -0.3190230 | -0.1802723 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.2431756 | -0.3637536 | 0.3171732 | 0.9013392 | -0.3637536 | 0.5685139 | 0.9821615 | -0.3637536 | -0.3637536 | -0.3170555 | 0.3741975 | -0.3637536 | 0.6605141 | -0.3637536 | -0.0402998 | -0.2471091 | -0.3637536 | -0.3637536 | -0.2911449 | 0.6399439 | -0.3637536 | 0.5926951 | 0.1909775 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2822850 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4096660 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2484860 | -0.0100250 | -0.3637536 | 0.6272671 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1316633 | -0.3637536 | -0.3637536 | 0.1396733 | -0.3637536 | 0.1296728 | -0.3637536 | -0.3637536 | -0.3524279 | -0.3637536 | 0.2754281 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3767861 | -0.3637536 | -0.2345170 | -0.3637536 | -0.0979465 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1138354 | -0.3637536 | 0.0111708 | -0.3637536 | -0.3637536 | 0.1399013 | -0.3637536 | -0.2376183 | -0.0420930 | -0.3637536 | -0.5909339 | -0.3637536 | -0.3637536 | 2.0633043 | -0.3637536 | -0.3637536 | 0.5172751 | -0.3637536 | 0.1296710 | -0.3377066 | -0.0300647 | 1.1558464 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.0482151 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 5.4424944 | -0.3637536 | -0.3637536 | -0.1002123 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4886591 | 4.9585702 | -0.0232198 | 0.1264820 | -0.3637536 | -0.3637536 | -0.3210991 | -0.3637536 | -0.3637536 | -0.1405586 | -0.3637536 | -0.3637536 | -0.3637536 | 0.3416746 | -0.3637536 | -0.3637536 | -0.0705465 | -0.3637536 | -0.3637536 | -0.3637536 | 0.6685000 | -0.3637536 | 2.9680833 | 0.1034080 | -0.0750636 | 0.2999960 | -0.3637536 | -0.3637536 | 0.7733317 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 3.3932448 | 1.0923297 | -0.1640512 | 0.1476696 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.9308886 | -0.3637536 | -0.3637536 | 1.2781851 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.7665539 | -0.3637536 | 0.1833848 | -0.3637536 | 1.8840935 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.2521668 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.1766863 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1212594 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1876036 | -0.3637536 | -0.3637536 | 5.3071251 | -0.2934708 | -0.3637536 | -0.3637536 | 0.0090392 | -0.3637536 | 1.5308853 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.2158504 | 2.6540079 | 0.9950975 | -0.3385181 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 4.0705010 | -0.3637536 | -0.3637536 | -0.3637536 | 17.8413978 | -0.3637536 | -0.3637536 | -0.0806256 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 6.7391205 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4579637 | -0.3637536 | -0.3637536 | 1.4616221 | -0.3637536 | 1.0468900 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1402633 | -0.3637536 | 0.4588884 | 1.1573010 | -0.3637536 | 0.2733271 | -0.3637536 | -0.3637536 | -0.3637536 | 1.4511216 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.5076422 | -0.3637536 | -0.0093276 | 0.4192004 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1282887 | -0.3637536 | 1.2526686 | -0.1924628 | -0.3637536 | -0.3637536 | 0.7697755 | -0.3637536 | -0.3637536 | 0.9571343 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1951579 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 1.8079866 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | 0.4711832 | -0.3637536 | -0.1161768 | -0.3637536 | -0.0398852 | 0.1471012 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.3637536 | -0.1377115 | -0.3637536 | -0.3637536 | -0.0709630 | -0.3637536 | -0.1143204 | -0.3637536 |
| Max_201310 | -0.2787139 | -0.2787139 | 2.2689856 | -0.2787139 | 0.3158198 | 1.5839023 | -0.2787139 | -1.0509373 | -0.2787139 | -0.2787139 | 0.5490824 | 0.3286893 | -0.1110626 | 0.9575268 | -0.2508827 | 1.0272650 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1808345 | 0.1429978 | -0.2787139 | -0.2787139 | -0.1344559 | -0.0681094 | -0.2787139 | -3.9933838 | -0.2787139 | -0.2787139 | 1.7539351 | -0.3297044 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4126444 | -0.2787139 | -0.2787139 | 1.3999297 | -0.2787139 | -0.1959465 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | 0.5481508 | -0.1602489 | -0.2787139 | 0.8305718 | 1.1047629 | -0.2787139 | 0.5927821 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3210618 | -0.2787139 | -0.2787139 | 0.5719032 | -0.2787139 | -0.2787139 | 0.7837799 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7863423 | 0.3911494 | -0.0742801 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0247301 | 1.0760101 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3643441 | 0.9465694 | -0.2787139 | -0.2787139 | 1.8994109 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4100361 | 0.4877690 | -0.2787139 | 0.2414582 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9030395 | -0.2787139 | 0.4320761 | -0.2787139 | 0.2240472 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | 0.5530035 | -0.1284247 | 1.0654350 | 0.2958709 | -0.2787139 | -0.2787139 | -0.1045580 | -0.2787139 | -0.2787139 | -0.2787139 | 1.3306971 | -0.2787139 | 1.0877215 | -0.1542168 | -0.2787139 | 0.7557342 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2107875 | 0.7795881 | -0.2787139 | -0.2787139 | 0.5686479 | -0.2787139 | -0.4576030 | 0.4798768 | -0.2787139 | -0.1297991 | -0.2787139 | -0.2787139 | 0.1393979 | 0.5000293 | -0.2787139 | -0.2787139 | 1.9292352 | -0.2787139 | -0.4388724 | -0.0397527 | 0.1938678 | 1.0776585 | -0.2787139 | -0.2193059 | -0.2787139 | 0.2386565 | -0.1779718 | 0.5208240 | 0.5323143 | 0.2272622 | -0.2168319 | -0.0065426 | -0.1103078 | 0.0766811 | 0.1181991 | 0.3155822 | -0.2787139 | 0.4772891 | -0.2787139 | -0.2787139 | 1.3811974 | -0.2787139 | -0.2787139 | -0.2787139 | 1.9044281 | -0.2787139 | 1.0068405 | 0.3982290 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.9468333 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6415028 | -0.2787139 | 0.2899181 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3649149 | -0.2787139 | 0.5074649 | -0.2787139 | -0.2787139 | -0.2839541 | -0.1033518 | 0.7182047 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.6829112 | -0.2787139 | 0.1407533 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2315560 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3332174 | -0.2787139 | 0.1655299 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9428356 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1956843 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0275878 | 0.0043692 | 2.2783133 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0100308 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.8456583 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2851193 | 0.5074133 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0741236 | -0.2787139 | -0.1481867 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9357276 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0761961 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.9760384 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2144499 | -0.0433120 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.3919119 | 0.6941844 | -0.2787139 | 0.5414284 | -0.1761742 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5110528 | 0.1585800 | 0.3923484 | 1.0052107 | 4.6382411 | -0.2787139 | 3.0713572 | -0.0045510 | -0.2787139 | -0.2787139 | 0.1647861 | 0.4651579 | 0.1468533 | -0.2787139 | 0.2308361 | -0.0676788 | 0.5705472 | -0.1589178 | -0.2787139 | 0.4932098 | 0.2330199 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0603254 | -0.2787139 | 0.3232358 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2718196 | -0.2787139 | 0.0573610 | -0.2787139 | -0.2787139 | 0.3796552 | 0.5426744 | -0.2787139 | 0.9517720 | -0.2787139 | -0.2787139 | 0.4013124 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9773127 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1624124 | -0.2787139 | -0.0421207 | 0.2276319 | -0.1747057 | -0.2787139 | 0.0399541 | -0.2787139 | 0.3383056 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4558710 | -0.2787139 | -0.2787139 | -0.2787139 | 1.3516550 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0592387 | 0.0934470 | 0.9137643 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0056065 | -0.2787139 | -0.0964122 | 0.8149775 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3044270 | 0.3484538 | 0.9392412 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0846319 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2741770 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1585180 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2345882 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0861692 | 1.1324929 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2459401 | -0.2787139 | 0.9851179 | 0.6573059 | 0.3136111 | 0.6772495 | 1.3176826 | -0.2787139 | 0.3072685 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2654626 | 0.4156196 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1708597 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7297557 | 0.2765809 | -0.2787139 | -0.1934522 | 0.1297875 | 0.9785132 | -0.0646261 | -0.2787139 | -0.2787139 | 1.5315549 | 0.1149541 | -0.2787139 | -0.2787139 | 0.5986960 | 0.3639964 | -0.2787139 | -0.0407936 | 0.5468687 | -0.2787139 | -0.2787139 | 0.0585549 | -0.2787139 | 0.2261598 | -0.2787139 | -0.2114156 | -0.0450011 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2316105 | 1.1734993 | 2.2149362 | 0.1042992 | 0.2289933 | 0.1962993 | 0.7033680 | -0.2787139 | -0.2787139 | 0.3535191 | -0.2787139 | 0.4503427 | -0.2223020 | -0.2787139 | -0.2787139 | -0.3796118 | 0.1289217 | -0.2787139 | 6.9091755 | 0.8311782 | -0.2787139 | -0.1710700 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1935862 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7721991 | 0.4882540 | 0.0783658 | 1.1995293 | 0.0309009 | -0.2787139 | -0.2787139 | 0.1904075 | 0.2012048 | -0.2787139 | 0.9714423 | -0.2787139 | 0.2145581 | -0.2787139 | 0.2095669 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6123927 | -0.2787139 | 0.1347832 | -0.2787139 | -0.2787139 | 0.1879664 | 0.8546080 | 1.8225427 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0160458 | 0.7508581 | 1.4475710 | 0.9793993 | -0.2787139 | -0.2787139 | 1.7047806 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9385412 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0211978 | 0.3146674 | 0.0360897 | -0.2787139 | -0.2787139 | 0.1320287 | 0.0330361 | 0.4990745 | -0.2787139 | -0.2787139 | -0.1621899 | -0.0063911 | -0.2787139 | -0.1172920 | -0.2787139 | -0.2787139 | 1.8885699 | 0.0610679 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2125300 | -0.2787139 | 1.2302190 | 0.0743634 | -0.2787139 | -0.2787139 | 0.7987460 | -0.2787139 | -0.2787139 | -0.2388816 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5956523 | 1.3667852 | -0.2787139 | -0.1219286 | 0.0848197 | -0.2787139 | -0.0584396 | -0.2787139 | -0.2787139 | 0.0894057 | -0.2787139 | 0.3136111 | 0.3885301 | -0.1531147 | 0.2359154 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9896715 | -0.2787139 | -0.2787139 | -0.1526671 | 0.1183977 | -0.2787139 | -0.2787139 | 1.6347472 | -0.1629193 | 1.4243848 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.4982612 | -0.2787139 | 0.2875392 | 0.4866395 | 0.0864140 | 1.9668095 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2078594 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4959876 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2607351 | -0.2787139 | -0.2787139 | 1.8993343 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0121145 | -0.2787139 | -0.2787139 | 0.8252272 | -0.2787139 | 2.5717415 | -0.2787139 | -0.1911296 | -0.1220172 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2427506 | 0.1577847 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2012528 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1208815 | -0.2787139 | -0.2787139 | 0.7159881 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1857744 | -0.2787139 | 0.5773846 | -0.2327954 | -0.2787139 | -0.0507125 | -0.2787139 | -0.0914756 | 0.7941937 | -0.2787139 | -0.2787139 | 0.0100391 | -0.2787139 | 0.0661156 | -0.2787139 | -0.1153431 | 0.2555129 | -0.2787139 | -0.2057692 | 0.2788509 | -0.2787139 | 4.8046677 | -0.2787139 | -0.1421237 | 1.8620962 | -0.2787139 | 1.2704659 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6414811 | -0.2787139 | 0.1393777 | 1.9094752 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.5603683 | -0.2787139 | -0.2787139 | 3.9261354 | 0.0078278 | 0.2944325 | 0.1124121 | -0.2787139 | -0.2787139 | 1.4210024 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1610041 | 0.9367298 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1006098 | -0.0427077 | 0.2171349 | -0.2787139 | 0.1906757 | -0.2787139 | 0.3982290 | -0.2787139 | -0.2787139 | 0.2038603 | -0.2787139 | 0.7855417 | -0.2787139 | 2.0832915 | 0.3474941 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0332727 | 0.2308894 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2197142 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3712350 | 0.7220467 | -0.2787139 | -0.2787139 | -0.0615896 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9826730 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2564576 | 0.2421478 | 0.9059361 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8704640 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5814274 | -0.2787139 | -0.2787139 | 0.1635583 | -0.1384123 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1553742 | -0.2787139 | 1.2403547 | -0.2787139 | -0.2787139 | 0.2884518 | -0.2787139 | 0.5110528 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8127818 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2033380 | 0.3136359 | -0.2787139 | 0.7311605 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2908360 | -0.2787139 | -0.2787139 | -0.0415930 | 0.3805508 | -0.2787139 | 0.3343381 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2179626 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1127961 | -0.1501392 | -0.2787139 | -0.2787139 | -0.2787139 | -0.6226445 | -0.2787139 | -0.2787139 | 1.4511145 | -0.2787139 | 0.4488913 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6456128 | -0.2787139 | 0.3483240 | -0.0732763 | -0.2787139 | 0.5110528 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1564054 | -0.2787139 | -0.2787139 | 0.4701999 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2558197 | -0.2787139 | -0.2787139 | 1.8324287 | -0.0258027 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1829506 | -0.2787139 | -0.2507458 | -0.2787139 | -0.2332253 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.6826584 | 1.5940360 | -0.2787139 | -0.2787139 | 0.5894547 | 1.0443085 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6708373 | -0.2787139 | 0.5702161 | -0.2787139 | -0.2787139 | -0.0837769 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0332768 | -0.2787139 | -0.2787139 | 1.9433938 | -0.2787139 | -0.2787139 | -0.1944754 | -0.2787139 | 0.4004390 | -0.2787139 | -0.2787139 | -0.0163346 | 0.3427354 | 0.6711130 | -0.2174967 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1298686 | 1.1205882 | -0.2787139 | -0.2787139 | 0.3968326 | -0.2787139 | 0.2935323 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8304633 | 0.3343189 | 2.9940843 | -0.2787139 | 0.6835624 | -0.2787139 | -0.2787139 | 0.5620852 | 0.6079110 | -0.2787139 | -0.2787139 | -0.1049232 | 0.1150447 | -0.2787139 | -0.2787139 | 1.8812299 | -0.1358254 | -0.2787139 | -0.2787139 | -0.1330396 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1228753 | -0.2787139 | -0.1491832 | -0.2787139 | -0.2787139 | 0.0290557 | -0.2787139 | 0.4748803 | -0.2787139 | -0.1470285 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2511230 | -0.2787139 | 0.6280437 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1793683 | -0.2787139 | 4.0149360 | 3.6767608 | 2.1776818 | -0.2787139 | -0.2787139 | -0.0288351 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8480150 | -0.2787139 | 0.8059900 | 3.7133211 | -0.2787139 | 0.2292406 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1310436 | 0.1126232 | 0.1571626 | -0.2787139 | -0.2471188 | -0.1158744 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2059157 | -0.0626858 | -0.1203029 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5033137 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3935248 | -0.2787139 | -0.2787139 | 1.3485560 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0400614 | 0.3438595 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2453347 | -0.2787139 | -0.2630131 | -0.2787139 | 0.1034579 | -0.2787139 | 0.2974130 | 0.3401839 | 1.6957028 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7834803 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.3782278 | 2.6599600 | -0.2487927 | -0.2787139 | -0.2787139 | -0.1842940 | -0.1751491 | 0.1444298 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1661806 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1978437 | -0.2787139 | 1.6013943 | -0.2787139 | 0.1827211 | 0.1385211 | -0.2787139 | -0.2787139 | -0.1244596 | -0.2787139 | -0.2787139 | 0.1796329 | -0.2787139 | 0.4779073 | 0.0554588 | -0.2787139 | -0.2787139 | 0.1289903 | 1.1656254 | -0.2787139 | -0.2787139 | 0.5119495 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1929871 | 1.4671708 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 3.3504603 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9533221 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1758217 | 0.2731228 | 0.3033435 | -0.0354728 | -0.2787139 | -0.2787139 | 0.2110096 | -0.2787139 | -0.2079026 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7114942 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6098660 | -0.2787139 | -0.2787139 | 0.3258845 | -0.2004939 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.6290983 | -0.2787139 | 2.7327880 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0495073 | -0.2532322 | -0.1906540 | -0.2787139 | -0.1480090 | -0.2787139 | 0.6019069 | -0.2787139 | -0.2787139 | -0.2787139 | 3.5133484 | -0.0082624 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0385300 | -0.2787139 | 2.3801927 | 0.1057480 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4910685 | -0.2787139 | -0.2787139 | 0.7479232 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0564528 | -0.2787139 | 0.2371419 | -0.2787139 | 1.7759815 | -0.1324240 | -0.2787139 | -0.2411928 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.8302923 | -0.2787139 | -0.2787139 | 0.0403170 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1479664 | -0.2787139 | -0.2787139 | 0.4108291 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1768792 | -0.2787139 | 0.5146363 | 1.1593817 | -0.2787139 | 0.4640587 | -0.2787139 | -0.2787139 | 0.2046735 | -0.2787139 | -0.2787139 | 0.2793882 | -0.2787139 | -0.2787139 | -0.2688922 | -0.2787139 | 0.3301528 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2152171 | 0.2897204 | 0.6589759 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2075308 | -0.2787139 | -0.2787139 | 0.1730892 | 0.2953387 | -0.2787139 | 0.1927555 | -0.2787139 | -0.2787139 | -0.1949313 | -0.0272987 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1088576 | 0.3024030 | -0.2787139 | 0.2646706 | 0.4560738 | 4.6939328 | -0.2787139 | -0.2787139 | -0.2438954 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2498106 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2434339 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6560978 | -0.2787139 | 3.7945261 | -0.2787139 | 0.5366417 | -0.2787139 | 2.7878878 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0512389 | 0.3393315 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.4841712 | -0.2787139 | 0.1954921 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.4871268 | -0.2787139 | -0.2787139 | 0.1096843 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0248644 | -0.2787139 | 0.4872236 | -0.2787139 | -0.2091590 | 0.7229902 | 1.8570524 | 0.8013848 | -0.2787139 | -0.0312254 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0222796 | -0.0632790 | -0.2787139 | -0.2787139 | 0.1655546 | -0.2787139 | 0.7299874 | -0.2787139 | -0.0793017 | 0.0433748 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1152638 | -0.2787139 | 0.3871571 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4224470 | -0.2787139 | -0.2787139 | 1.1548317 | -0.1755956 | -0.2787139 | -0.2787139 | 2.2329314 | 0.5656098 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0343435 | -0.2787139 | -0.2787139 | 0.0029711 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3662215 | 0.2691714 | -0.2787139 | -0.1835159 | 0.1718129 | -0.1714382 | -0.2787139 | 0.2598000 | -0.1723557 | -0.2787139 | 0.0650960 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0427110 | -0.2471102 | 0.8920373 | -0.2787139 | -0.2787139 | -0.1842085 | 4.0916086 | 0.8160083 | -0.2787139 | 0.6853052 | -2.2090320 | -0.2787139 | -0.0969497 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.3440696 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2616789 | 0.0067808 | -0.1965315 | -0.2787139 | 0.0106711 | -0.2787139 | 0.4320761 | 0.2197689 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0767045 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0653883 | 0.5429992 | -0.2787139 | 0.3614384 | -0.2787139 | -0.2787139 | 0.0448548 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0280371 | -0.2787139 | 0.1999194 | -0.2787139 | -0.3233597 | 0.2396204 | 0.4943601 | -0.2787139 | -0.2787139 | 1.1364078 | 1.0023406 | 0.6924744 | -0.2787139 | -0.2094057 | 0.2592289 | -0.2787139 | 0.5408088 | -0.0969975 | -0.2787139 | 3.5238000 | 0.9182589 | -0.0551164 | -0.0370288 | -0.2787139 | 1.0902514 | 0.3552299 | -0.0458207 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7174599 | 0.2338700 | -0.2787139 | 2.3658066 | 0.3943812 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2313515 | -0.2787139 | -0.2787139 | 0.9026126 | -0.2787139 | -0.0533941 | -0.2787139 | -0.2787139 | 1.1215772 | 0.5630625 | 0.3411686 | -0.2787139 | -0.2787139 | -0.2447563 | 0.0820437 | -0.5072568 | 0.6347528 | -0.1942523 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2103739 | 0.6305599 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1443056 | 0.3363644 | -0.1460012 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4405602 | 1.0682762 | 1.0394203 | -0.2787139 | -0.1920617 | -0.2787139 | 0.7991102 | -0.2787139 | -0.2787139 | 0.4651560 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0982351 | -0.2787139 | 0.1022375 | 2.4027944 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4533941 | 0.3291038 | -0.1462482 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2582198 | -0.0303259 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0597346 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2668815 | 0.7445451 | 0.2638861 | -0.1849167 | 1.1553414 | -0.0219768 | 0.2219623 | -0.1043751 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | 0.8975344 | -0.1944758 | 0.1071804 | 1.2357494 | 0.6577554 | -0.2787139 | -0.1963952 | 0.3816526 | -0.2787139 | -0.3763499 | -1.6863168 | -0.2787139 | -0.2787139 | -0.0814654 | 0.9221642 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4957167 | -0.2787139 | -0.0699132 | 0.0050184 | -0.2787139 | 0.6304495 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2530086 | 0.5607174 | -0.2787139 | -0.2445932 | -0.2787139 | -0.0159414 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | 0.6857885 | -0.2787139 | -0.2787139 | 1.0398560 | -0.2787139 | 0.3253018 | 0.2413982 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1708009 | -0.2787139 | -0.1862940 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1840400 | -0.2787139 | -0.2787139 | -0.1237129 | -0.2787139 | -0.0015913 | -0.2787139 | -0.2787139 | 1.3701774 | -0.2787139 | 0.3299242 | -0.2787139 | 0.9492556 | 0.3057658 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2029008 | -0.2787139 | -0.2787139 | 0.4377982 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8960805 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.9403127 | 0.3236134 | -0.1525791 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2908611 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1362032 | -0.2787139 | -0.2787139 | 0.0856341 | -0.2787139 | 0.7003580 | -0.1013660 | -0.2787139 | -0.2787139 | -0.1893671 | -0.2787139 | 0.7841606 | 1.7599655 | -0.1389827 | 2.4940584 | -0.2152250 | -0.2787139 | -0.2787139 | 0.3759031 | 0.7053646 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2158807 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4839526 | -0.1898389 | 0.0281411 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1575429 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0926760 | -0.2787139 | 0.1524141 | 1.1207296 | 0.1166432 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -3.2302934 | -0.2787139 | -0.8623991 | -0.2787139 | 0.2666797 | 0.6139686 | -0.2787139 | -0.2787139 | -0.0306082 | -0.2787139 | -0.2787139 | 0.7834849 | 0.2641276 | -0.2787139 | -0.2787139 | -0.0038122 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4039927 | -0.2787139 | -0.2787139 | 0.7909257 | -0.2787139 | 0.5199626 | -0.2787139 | -0.1577060 | -0.2787139 | -0.2787139 | 0.4507171 | 0.3035717 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5783710 | -0.2787139 | 3.0333577 | -0.2787139 | -0.2787139 | -0.2787139 | 1.4982612 | -0.2787139 | -0.2787139 | -0.1105013 | -0.0922001 | -0.1736033 | -0.2787139 | 0.3136339 | -0.2787139 | 0.0902083 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3101446 | -0.2787139 | 0.3571566 | 0.4491856 | -0.2787139 | -0.2787139 | 0.2892573 | -0.2787139 | -0.2787139 | 0.1068637 | 0.2735050 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0032347 | -0.2787139 | -0.2787139 | 1.0638895 | -0.1668422 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0353577 | -0.2787139 | -0.2787139 | 0.4644307 | -0.1548858 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5556573 | 2.6257955 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3065630 | 0.2828257 | -0.2787139 | -0.2787139 | 0.6206351 | -0.3147434 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4883201 | -0.2725981 | -0.2787139 | 49.2184505 | -0.2787139 | -0.2787139 | 0.0593673 | 0.3577288 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3635974 | 2.6726328 | 8.7153505 | 2.1820312 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0079890 | 2.8121921 | 0.2930284 | 0.1496070 | 0.6522663 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0673740 | -0.2441471 | -0.2787139 | -0.2787139 | 17.7282172 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5008986 | 0.3085327 | 0.5238073 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1027770 | -0.2787139 | -0.2787139 | 0.4144918 | -0.2787139 | 14.3751400 | -0.2787139 | -0.2787139 | -0.2564933 | -0.1907200 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0712007 | -0.2787139 | -0.1198082 | 2.7823280 | -0.2787139 | -0.2787139 | 0.1315364 | -0.2787139 | -0.2787139 | -0.2479096 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1064020 | 1.1815693 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.3001015 | -0.2787139 | -0.2787139 | -0.1987157 | 0.2779003 | 0.1679526 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2440687 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9991080 | 0.3136111 | 0.7642240 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0458163 | -0.2177814 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2302333 | -0.2787139 | -0.2787139 | -0.2683646 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3358233 | -0.2787139 | 0.2185858 | -0.4042325 | -0.2787139 | -0.0184984 | -0.2787139 | 0.5162316 | -0.2787139 | -0.0900938 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3578408 | -0.2787139 | -0.2787139 | 0.7078264 | 1.7136108 | 1.0928324 | -0.2787139 | -0.2787139 | 0.0194064 | -0.2787139 | 1.7300900 | 0.3166478 | -0.2787139 | -0.2787139 | 1.3576900 | -0.2787139 | 0.0125584 | -0.2787139 | 0.0609688 | -0.2391265 | -0.2787139 | -0.2787139 | 0.2060697 | -0.0028060 | -0.2787139 | 0.1801414 | -0.2787139 | 0.1839031 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8117343 | 0.4927582 | -0.2787139 | 0.3824395 | -0.2787139 | -0.2787139 | 1.7375454 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0207599 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1820011 | 0.9054465 | -0.2787139 | -0.2787139 | -0.0323498 | -0.2787139 | -0.2787139 | 0.6571342 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1934802 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6711487 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4221136 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4347461 | -0.2787139 | 0.3879082 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2824529 | -0.2787139 | 3.7816646 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4847142 | -0.2787139 | 0.8617531 | -0.2787139 | 1.3653981 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2650388 | -0.2787139 | -0.2787139 | 0.6176282 | -0.2787139 | -0.2787139 | 0.0085791 | -0.2787139 | -0.2787139 | -0.1437398 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3531601 | 0.2622413 | -0.2787139 | 0.1951461 | -0.2787139 | -0.2787139 | 0.1817105 | -0.2787139 | -0.2787139 | 0.1037933 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2047949 | -0.2787139 | -0.2625509 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2524743 | -0.2787139 | 0.3039416 | 0.4628648 | -0.2787139 | -0.2787139 | 0.7836963 | -0.2787139 | 0.7530781 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9465221 | -0.2002970 | -0.2787139 | 0.2158160 | -0.2787139 | -0.2787139 | 0.5110528 | -0.2787139 | 0.7156650 | -0.2787139 | 0.3028732 | 0.4615638 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3716907 | 1.5517488 | 5.8945763 | -0.3791395 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0406922 | 1.2061083 | -0.2787139 | -0.2787139 | 0.3136111 | 0.8097891 | -0.2787139 | 0.1443754 | -0.2787139 | -0.0908332 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0142708 | 0.8506490 | 0.3184335 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4711602 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.5041812 | -0.2787139 | -0.2787139 | 1.0440708 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1728805 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8032850 | -0.1416730 | -0.2787139 | -0.2787139 | 0.3392851 | -0.1852954 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0025001 | -0.2787139 | 0.2691626 | -0.2787139 | 0.4942735 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7880994 | -0.1233645 | 0.7691951 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5148433 | 0.0949400 | -0.0627293 | -0.2787139 | -0.2787139 | -0.0499450 | -0.2787139 | -0.2787139 | 0.3704504 | -0.2526776 | -0.2787139 | 1.8971585 | 0.2412490 | -0.2787139 | -0.2787139 | -0.0989973 | 0.9139392 | -0.1731181 | -0.2787139 | -0.2787139 | 1.3167517 | 0.4784393 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5059244 | -0.2787139 | -0.1570824 | 0.6185768 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0121676 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5384612 | -0.2787139 | -0.2787139 | 0.5481596 | -0.2787139 | 5.3300640 | 0.1359652 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7565883 | -0.2787139 | 2.0689729 | -0.2787139 | -0.0102266 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0812722 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1216238 | -0.2787139 | 0.1076558 | 0.0359892 | -0.2787139 | 0.1848523 | -0.2787139 | -0.2787139 | 0.9526932 | 3.1985949 | -0.2787139 | 0.4958289 | -0.0526859 | -0.2787139 | -0.2787139 | -0.2308740 | -0.0221316 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7676801 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1449526 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0950489 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0881781 | 0.5206961 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2049661 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1161695 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4899609 | 0.2859312 | 1.1200385 | -0.2787139 | -0.1321681 | -0.2787139 | 0.1846833 | -0.2787139 | -0.2787139 | 0.2461917 | -0.0881536 | -0.2787139 | 0.3920457 | -0.2787139 | 0.4580997 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4615535 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0379062 | -0.2787139 | -0.2787139 | 0.2824092 | -0.2787139 | -0.2787139 | 0.1807632 | 0.6650092 | -0.2787139 | -0.1958521 | -0.2787139 | 0.7874711 | -0.2787139 | -0.1022658 | -0.2787139 | 0.9060076 | -0.2787139 | 0.6139180 | -0.2787139 | -0.2787139 | 0.4254697 | -0.2787139 | -0.0076338 | -0.1351997 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3775318 | -0.2787139 | -0.2787139 | 2.3326529 | 0.0400089 | -0.1109412 | 0.8672912 | -0.2787139 | 0.8789297 | -0.2787139 | -0.2787139 | 0.4444913 | -0.2787139 | -0.2608156 | 0.2863167 | -0.2787139 | 0.8845814 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3622756 | 0.2928640 | -0.2855272 | -0.2787139 | 1.0799602 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2105774 | -0.2787139 | 1.0015180 | 0.1325355 | 0.3136111 | 0.4574919 | -0.2787139 | 0.2564379 | -0.2787139 | -0.2787139 | 0.1309975 | 0.9454245 | -0.2787139 | -0.2787139 | 2.6402394 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | 0.4487491 | -0.2787139 | 0.6985896 | -0.2787139 | -0.2787139 | -1.1164486 | 0.3136111 | -0.2787139 | -0.2787139 | -0.1875160 | 0.6698784 | -0.1710567 | -0.2787139 | -0.2787139 | -0.2787139 | 4.3540338 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0758534 | -0.2787139 | -0.2787139 | 4.9364105 | -0.2787139 | -0.2787139 | 0.3992710 | 0.0750767 | -0.2787139 | -0.2787139 | -0.2006794 | 2.0856893 | -0.2541979 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0046205 | 0.3752934 | -0.2787139 | -0.2551419 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.5301843 | -0.2787139 | 0.1646364 | 0.6689934 | 0.1974109 | -0.2017729 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2181027 | -0.2787139 | -0.2787139 | 0.4751195 | -0.2787139 | 0.5222969 | -0.2787139 | 0.7116167 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | 0.3157574 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9240924 | -0.2787139 | -0.2787139 | 0.5603709 | 1.4044856 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0580560 | 1.0941564 | -0.2787139 | 1.1102409 | 1.7649121 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.9024440 | 0.1466816 | -0.0622208 | -0.0868204 | -0.2787139 | 1.0943797 | 0.1658934 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2172326 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1078671 | 1.9631656 | -0.2787139 | 0.4137837 | -0.1922883 | 0.2364779 | -0.2787139 | 0.3052260 | -0.2237768 | 4.1219882 | 0.6287584 | 1.1949324 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 3.9545937 | -0.2787139 | -0.2787139 | 0.7254795 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 3.2186505 | 1.0279064 | -0.1820925 | 0.4296623 | 0.1231859 | -0.2787139 | 0.1168474 | 1.2790159 | 0.3159521 | -0.2787139 | 0.3105444 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3530083 | -0.2787139 | 0.0706200 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.4607722 | 1.0320251 | -0.2787139 | -0.2135734 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2823338 | -0.0944063 | -0.2787139 | -0.2787139 | -0.1283697 | -0.2787139 | -0.2787139 | -0.0606422 | 0.2894340 | -0.0611453 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1108141 | 0.4354682 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7180895 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2596846 | -0.2443852 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0937748 | -0.2787139 | 0.5831158 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0845650 | -0.2787139 | 0.6864465 | -0.2787139 | -0.2787139 | 0.0141653 | -0.2787139 | -0.2399480 | -0.2787139 | 0.8642859 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2779809 | 0.9386761 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6067329 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4238479 | -0.2787139 | -0.2787139 | -0.2727966 | -0.2787139 | 1.4346893 | -0.2787139 | -0.2787139 | -0.1251812 | -0.2787139 | -0.2787139 | -0.2787139 | -0.4700972 | -0.2787139 | -0.2787139 | -0.2005782 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5355099 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4416814 | -0.2787139 | 0.1137563 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1774405 | -0.2787139 | 0.4192008 | -0.2787139 | -0.2787139 | -0.2787139 | 4.6590619 | -0.2787139 | -0.2787139 | 0.2292767 | -0.2787139 | -0.2582102 | -0.2787139 | -0.2787139 | 1.2446690 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1940960 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1871581 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4504999 | -0.2787139 | -0.1604118 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0876182 | -0.2787139 | 0.2281939 | -0.2787139 | 0.2254457 | -0.2787139 | 0.3496194 | -0.2787139 | 1.1599045 | -0.2787139 | 0.2487255 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2475007 | -0.2787139 | 1.0215176 | -0.2787139 | 0.7211578 | 2.1489290 | -0.2787139 | -0.2787139 | 0.3274853 | -0.1751185 | 0.9964163 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4214312 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1620575 | -0.2787139 | 0.0950373 | -0.0393355 | 0.8248911 | 0.3806385 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.7074929 | -0.2787139 | -0.2787139 | -0.1713407 | -0.2787139 | 0.3069803 | -0.2787139 | 1.6946090 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1143157 | -0.2787139 | -0.2216562 | 0.0864265 | -0.0886784 | -0.2787139 | 1.2205819 | -0.1589171 | 0.1448919 | -0.2787139 | -0.2431433 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1149878 | -0.2787139 | 0.3376042 | -0.2787139 | 0.2931028 | -0.1623278 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8520807 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2744025 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9729533 | -0.2787139 | -0.2787139 | 0.9170288 | -0.2787139 | -0.0351042 | 1.0756878 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2428205 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0446614 | 0.2932537 | -0.2658617 | -0.2787139 | -0.2787139 | 0.0789681 | -0.2581230 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3435304 | 1.1724175 | -0.2787139 | -0.2787139 | 0.2900048 | 0.7958995 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2448068 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | 1.0548851 | -0.2787139 | -0.2787139 | 0.3501069 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3612254 | -0.2787139 | 0.3913571 | -0.2787139 | 0.7439564 | -0.2787139 | -0.2787139 | 0.5156173 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3617608 | 0.3333128 | -0.2787139 | -0.2475093 | 0.3459873 | -1.1972965 | -0.2787139 | -0.2309693 | 1.9320732 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2944816 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1013241 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0943935 | -0.1706158 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2226901 | -0.1830204 | -0.2787139 | -0.2787139 | 0.3683936 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1993708 | -0.2787139 | -0.2787139 | 0.3550752 | 0.4763427 | 1.7685604 | 1.0068597 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5576333 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2356999 | 1.4448899 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0268506 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1329344 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4336547 | -0.2787139 | -0.2658858 | -0.2787139 | 0.2402025 | -0.2234053 | -0.1802510 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5835417 | 0.5613928 | -0.2787139 | 0.4328205 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7084945 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2701994 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8716068 | 1.1874771 | -0.2787139 | 0.2325542 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2573997 | -0.2787139 | -0.2787139 | -0.0799437 | 0.6814883 | -0.2787139 | 1.4499176 | -0.1113565 | 0.3136225 | -0.2787139 | 0.3972612 | -0.2787139 | -0.2787139 | 0.8114549 | -0.2787139 | -0.2787139 | -0.1367302 | 0.1864400 | -0.2787139 | -0.2787139 | 0.0249263 | -0.0513568 | -0.2787139 | 0.6262332 | -0.0500965 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5768637 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0247944 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.3821774 | -0.2787139 | 1.0020414 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2660593 | 0.3136111 | -0.2787139 | -0.2787139 | 0.2576112 | -0.2787139 | 0.4123320 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0913589 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1908318 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8161527 | -0.1672549 | 0.1221226 | 0.4060534 | 0.3195919 | -0.2787139 | -0.0705968 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1014537 | -0.2787139 | 0.6097736 | -0.2787139 | -0.2787139 | -0.0080729 | -0.2787139 | 0.6894635 | 0.1549954 | 0.5221750 | -0.2787139 | -0.2787139 | -0.2787139 | 4.1117499 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1048419 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2126212 | -0.2787139 | 0.2711683 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2626914 | -0.0665438 | 0.0838681 | -0.2787139 | -0.2787139 | 0.3208683 | 0.6376216 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7497961 | -0.2787139 | -0.2787139 | -0.1046631 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9484050 | 0.8666480 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | 0.6884281 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0916639 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4902695 | -0.2787139 | -0.2865386 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0379246 | 0.3030339 | 2.0833527 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3136111 | 0.5890858 | -0.2787139 | -0.2009517 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1920238 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5522995 | 0.8975344 | -0.2787139 | -0.1821572 | -0.2787139 | -0.2787139 | 0.4197826 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9328512 | -0.2267702 | 0.1264183 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2797008 | -0.2787139 | -0.2548362 | -0.2787139 | -0.2787139 | -0.1426569 | -0.2787139 | -0.2787139 | -0.0811400 | 0.3136111 | -0.2787139 | -0.2787139 | 1.6623432 | 0.9668514 | 3.3558323 | -0.2787139 | -0.2787139 | -0.0358913 | 1.0253771 | -0.2787139 | 0.0983475 | 0.2796012 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1837350 | -0.2787139 | -0.2787139 | 1.3045107 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5674647 | -0.2787139 | 0.2281869 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 3.0825723 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4059879 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4420332 | 1.2695429 | 0.1552239 | 0.1600794 | -0.1630583 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1284109 | 0.1652074 | -0.2787139 | -0.2787139 | -0.1819318 | 0.9044951 | 0.5865768 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8902985 | 0.2559952 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3761536 | -0.2787139 | -0.1792123 | 0.2289933 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8857433 | -0.2787139 | 0.6245207 | -0.2787139 | -0.2787139 | -0.1264114 | 3.1764190 | 0.2104373 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0684769 | -0.2787139 | -0.2787139 | 0.0675556 | -0.2787139 | 1.3206219 | -0.2787139 | -0.2787139 | -0.1865805 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2486103 | -0.2787139 | -0.2787139 | 0.3897035 | -0.0834721 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6184274 | 0.8523949 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.9963011 | 1.4930672 | 1.6063132 | 0.1577160 | -0.2787139 | 1.0279338 | -0.2787139 | -0.2538586 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7861024 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4849367 | -0.2787139 | -0.0057302 | -0.2787139 | -0.2787139 | -0.2787139 | 1.5046180 | -0.2787139 | 0.5661968 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7922062 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5630111 | -0.0979657 | -0.2787139 | 0.9071450 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2788782 | 4.2279991 | -0.2787139 | 0.4661816 | 8.4732138 | -0.2787139 | -0.2787139 | 0.5486358 | -0.2787139 | -0.1994170 | -0.2787139 | -0.2787139 | 0.4996429 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2377070 | 0.1322237 | -0.2787139 | -0.2787139 | 2.3857515 | -0.2787139 | -0.1115186 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 6.2787349 | 0.0239419 | 1.8285179 | -0.2787139 | -0.2787139 | 0.2747794 | -0.2787139 | 0.7204311 | -0.2787139 | 0.1504403 | 1.0256726 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0762976 | 1.3472813 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9465398 | -0.2787139 | -0.2787139 | 0.3315308 | 6.4841312 | 0.8870304 | -0.1049691 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9272723 | 0.4363847 | -0.2163214 | -0.2787139 | -0.2787139 | 0.1115238 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.7228537 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0644133 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.7714990 | -0.2787139 | 0.3525476 | -0.2787139 | 0.6337158 | 0.1992123 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0449088 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7356185 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8774202 | -0.2787139 | -0.2787139 | 0.2059157 | 0.1563843 | -0.2787139 | 0.4388204 | -0.2787139 | -0.2787139 | 0.3136111 | -0.2787139 | -0.2787139 | -0.2372837 | -0.2787139 | -0.2787139 | 0.3021108 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1308114 | 0.3794280 | -0.0904375 | -0.2787139 | -0.2787139 | 0.9263840 | -0.2787139 | -0.2787139 | -0.0870110 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0903530 | -0.0880487 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7208346 | 0.2158252 | -0.2787139 | -0.2787139 | 0.3811970 | -0.2787139 | -0.2787139 | 1.8928682 | -0.2787139 | -0.1023510 | -0.0518974 | -0.2787139 | -0.2185829 | -0.2787139 | 0.3483918 | 5.0673205 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0177567 | -0.2787139 | 0.3748520 | -0.2787139 | 0.4174176 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1877886 | -0.0730834 | -0.2787139 | 0.0999414 | -0.2787139 | 0.8900759 | -0.1447329 | -0.2053672 | -0.2787139 | -0.2787139 | -0.2787139 | 1.7821303 | -0.2787139 | 0.4043177 | -0.2044323 | -0.2787139 | -0.2787139 | 0.2596254 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0198807 | -0.2787139 | 0.1819120 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.9956958 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2027970 | -0.2008562 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2655950 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4360856 | 0.2140427 | 0.8373650 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3090896 | -0.2787139 | -0.2787139 | 0.4695876 | 0.1561227 | 0.2460908 | -0.2787139 | -0.2787139 | -0.3062061 | 1.1482509 | 0.0535320 | -0.1406482 | -0.2787139 | -0.0677325 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3117187 | -0.2787139 | 0.5562701 | 0.0077697 | -0.2787139 | -0.2787139 | 0.1478044 | -0.2787139 | -0.1714086 | -0.2787139 | 0.2829736 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1579252 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3693840 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0503556 | -0.2787139 | -0.1854138 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7049215 | -0.2787139 | 0.4607937 | 0.3136111 | 0.0108014 | -0.2787139 | 0.2900755 | 1.8957259 | -0.0838770 | 0.5139628 | -0.2787139 | -0.2787139 | -0.2787139 | -0.5979221 | -0.2787139 | 0.0146746 | -0.2370660 | 0.2782463 | -0.2787139 | -0.2123818 | -0.2787139 | 0.3787223 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0679593 | 0.0882346 | 1.1233759 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1884552 | -0.2787139 | -0.2787139 | 0.8093411 | -0.2787139 | 3.5521199 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.8634247 | -0.2787139 | 0.3352566 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1426227 | -0.0521434 | -0.2787139 | -0.2787139 | 1.6626701 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.4896653 | 0.3175425 | -0.2787139 | 0.7101316 | -0.2787139 | -0.2787139 | -0.0967157 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8263807 | 0.5634178 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3859562 | -0.2787139 | 1.0785891 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0492712 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5357027 | -0.2787139 | -0.2787139 | 0.0389375 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6559028 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2176187 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2320853 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5473236 | 0.3084159 | 0.1000325 | -0.2787139 | -0.2787139 | 0.8801681 | -0.2787139 | 0.8836161 | -0.2787139 | 0.3136111 | -0.1449631 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9150141 | -0.2787139 | -0.2787139 | 1.0732518 | -0.2787139 | 2.1267157 | -0.2787139 | -0.2787139 | 0.4307669 | -0.2787139 | -0.2787139 | -0.1938866 | -0.2787139 | 2.8306560 | -0.2787139 | -0.2787139 | 0.2859420 | -0.2787139 | 0.6228125 | -0.1099002 | 0.0710878 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5401342 | 0.3096757 | 0.7298838 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2575137 | -0.2787139 | -0.2787139 | 0.0190729 | -0.0602547 | 0.6274262 | -0.2787139 | 0.8449036 | -0.2787139 | -0.2787139 | 0.9274002 | -0.0452654 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0252360 | -0.0983547 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1686302 | 0.2995873 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.2403959 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5062087 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1434383 | 0.1890837 | 0.6362455 | -0.2787139 | 1.1224631 | 0.6248265 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0538206 | 0.5025801 | 0.4769584 | -0.2787139 | -0.2787139 | -0.2457684 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3197143 | 1.0376556 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0369691 | -0.2787139 | -0.2787139 | 0.3725803 | 0.8839845 | -0.2787139 | -0.0967409 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4332810 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4413297 | 0.3136111 | -0.2381547 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5477015 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6757687 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3015261 | -0.2787139 | -0.2787139 | 0.3890955 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3222211 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1504532 | 0.5237387 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4584266 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.6551543 | -0.2787139 | -0.2618445 | -0.2787139 | 0.8093621 | -0.2787139 | -0.2787139 | 0.5636846 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4449806 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3447861 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1459595 | -0.0754978 | -0.2787139 | 0.2778395 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0272594 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0124562 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4117666 | 1.0717992 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.3219214 | -0.2787139 | -0.2787139 | 0.2337692 | -0.2787139 | 0.3317300 | 0.3543391 | -0.2787139 | -0.2787139 | -0.1863983 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0246638 | 2.8635919 | 0.6520294 | -0.2787139 | -0.0505495 | -0.2787139 | -0.2787139 | 1.5527051 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.9877431 | -0.2787139 | 0.4757186 | 0.2367564 | -0.2787139 | -0.2787139 | 0.2646846 | -0.2787139 | -0.2787139 | 0.2539743 | -0.2787139 | 0.5630111 | 0.1955878 | -0.2787139 | -0.2787139 | 0.1470312 | -0.2787139 | 0.2097840 | -0.2787139 | -0.2787139 | -0.2636728 | 1.0232733 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0166232 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1630857 | -0.2787139 | 0.6020072 | -0.2787139 | -0.7267729 | -0.0331428 | 0.4105174 | -0.2787139 | 0.6906405 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2713492 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6782993 | -0.2787139 | -0.2787139 | -0.0096848 | -0.2787139 | -0.2062793 | -0.2787139 | 0.7679649 | -0.2787139 | -0.2787139 | -0.2787139 | 2.1442634 | -0.2787139 | 0.3541685 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1106090 | 0.4883322 | 0.3933907 | -0.2787139 | 0.2929171 | 0.4891972 | -0.2787139 | 0.3506314 | -0.2787139 | 5.2130062 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8732110 | -0.2787139 | 0.2797817 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2596518 | 0.2930703 | -0.2787139 | 0.3561999 | -0.2787139 | -0.1985196 | -0.2787139 | -0.2787139 | 0.5780419 | -0.2787139 | -0.2787139 | 0.3791360 | 0.5058366 | 1.0306012 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2559518 | -0.1306534 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.1706192 | -0.2787139 | 0.2216216 | 1.9081791 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5355663 | 0.3423732 | 0.0772845 | 0.4287201 | -0.2787139 | 0.3136111 | -0.2787139 | -0.0665723 | -0.2335856 | -0.2787139 | -0.2787139 | -0.1626552 | -0.2787139 | -0.2787139 | 0.1927689 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2860260 | 0.4960651 | -0.2787139 | -0.2787139 | 3.7417268 | -0.2787139 | 0.0633548 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4864321 | -0.2787139 | -0.2787139 | 2.0770337 | -0.2787139 | -0.2560535 | 0.5925771 | 0.2329280 | -0.2787139 | -0.2787139 | 0.4603771 | -0.2787139 | -0.2787139 | -0.2092756 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5458766 | 0.6714629 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2712578 | -0.2787139 | 0.3715222 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2583214 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.9538505 | -0.2551716 | 0.0254446 | -0.2787139 | -0.2787139 | 0.8467551 | 0.3586105 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5544938 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 3.1803567 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1041662 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1137784 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0642659 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1161940 | 0.1552843 | 0.5867067 | -0.2787139 | -0.2787139 | 0.2399445 | -0.2787139 | 2.7124427 | -0.2174086 | -0.2787139 | 3.9473830 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0789602 | -0.0828367 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1571574 | -0.2787139 | -0.2787139 | 0.5387107 | 0.3750898 | 0.7975488 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.7992704 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.2976023 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1309252 | -0.2787139 | -0.2787139 | 2.9073819 | -0.2787139 | 0.2814145 | 1.0458784 | -0.2787139 | 2.1149721 | -0.2787139 | 0.8319048 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3678540 | 1.9618580 | -0.1030255 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5008831 | 0.3714864 | -0.2787139 | -0.2787139 | -0.0828335 | -0.2787139 | -0.0744906 | 1.3859213 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2604303 | -0.2787139 | -0.2787139 | 0.3545896 | -0.2787139 | -0.2787139 | 0.0319608 | 0.0407218 | 0.3928537 | -0.2787139 | -0.2787139 | 0.6639400 | -0.2787139 | 2.9167630 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 11.3021934 | -0.2787139 | -0.2787139 | 2.6005180 | 1.0713553 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0535744 | 0.9422082 | 0.1353340 | -0.2787139 | 2.4678831 | -0.2787139 | -0.2787139 | 0.3690856 | -0.2787139 | -0.2787139 | 0.6534577 | -0.2787139 | -0.2787139 | -0.0584258 | 1.2771128 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0251274 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3496768 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.1177101 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1951795 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.3576881 | -0.2235250 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1936817 | -0.2787139 | 0.3162802 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.8533216 | 0.5818438 | -0.2787139 | -0.2787139 | -0.2787139 | -0.0629219 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.0184307 | -0.2787139 | 0.1933549 | 0.2661401 | -0.2787139 | 0.3823347 | 0.4672545 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3117690 | 0.3788557 | -0.2787139 | -0.1295971 | -0.2787139 | -0.1731059 | -0.2787139 | -0.1225877 | -0.2787139 | -0.2787139 | 0.6342796 | -0.2787139 | -0.2787139 | 0.2482852 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1546762 | 0.7025586 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4160433 | 1.3689068 | 0.4509155 | 0.6347802 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.0857938 | 0.1832748 | -0.2787139 | 1.9600169 | -0.2787139 | -0.2787139 | 1.1010692 | -0.2787139 | 0.8529556 | -0.2787139 | -0.2787139 | -0.2787139 | 2.8226469 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1458366 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2166787 | -0.2787139 | 0.3127706 | -0.0574108 | 1.9188269 | -0.0852898 | -0.2787139 | 0.7450497 | 0.9806482 | -0.2787139 | 1.4070153 | 0.9855043 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1178683 | -0.2787139 | 0.1185845 | 0.3090801 | -0.2787139 | -0.2787139 | 2.4725143 | 0.0926270 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 6.7125921 | -0.2787139 | -0.2787139 | 0.0447523 | 0.6426885 | -0.2787139 | -0.2787139 | 0.2918957 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2306762 | 10.8006966 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.8746069 | 0.4621567 | -0.1057901 | -0.2787139 | 1.0214970 | 3.5689971 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1450896 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2048839 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3748267 | -0.2787139 | -0.1670755 | -0.2787139 | -0.2787139 | 0.1995401 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.0669524 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -2.0556889 | -0.2787139 | 0.2910835 | -0.2787139 | 1.3079921 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 2.7137016 | -0.2787139 | -0.2787139 | -0.2787139 | 1.2944232 | -0.2787139 | -0.2787139 | -0.2787139 | 0.1208139 | 0.2807745 | -0.2787139 | 0.0673633 | 3.8431915 | 0.0351307 | -0.2787139 | 1.1714018 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5569743 | -0.2787139 | -0.2787139 | -0.0900030 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 1.6628112 | -0.2787139 | 0.4545402 | -0.2787139 | -0.0752920 | 2.0509131 | 2.5260602 | -0.1777742 | -0.2787139 | -0.2787139 | 0.9020144 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4482496 | -0.2787139 | 1.7700490 | 0.8085915 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1964914 | -0.2787139 | -0.2787139 | -0.2787139 | 0.8630641 | -0.2787139 | 0.8032710 | -0.0132668 | 5.0456325 | -0.1130175 | -0.2787139 | -0.2787139 | -0.2328079 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.6701802 | -0.2787139 | 0.9424038 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4501235 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.7271070 | -0.1362575 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2021758 | 0.0810989 | -0.2787139 | 0.8833878 | -0.2787139 | -0.2787139 | 0.3092482 | 0.9455066 | -0.2787139 | -0.2787139 | 1.6547311 | -0.2787139 | 0.6671988 | -0.2787139 | 0.3867084 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2616327 | 1.3964916 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.4354722 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.1628242 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.5597647 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.3010813 | 1.1055217 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | -0.2787139 | 0.9767576 | -0.2787139 |
| Max_201311 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | -73.9526888 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 | 0.0135197 |
| Max_201312 | -0.3160999 | 0.3290033 | 0.0492077 | 0.7641744 | -0.3160999 | 0.1503852 | -0.3160999 | 0.4494435 | 0.4152202 | 0.2430983 | -0.3160999 | -0.3160999 | 1.9457632 | -0.3160999 | 0.0965826 | 0.9107457 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2081118 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8151200 | -0.1399865 | 0.4834788 | -0.0864390 | 0.2496433 | -0.3160999 | 0.5820505 | -0.3160999 | -0.1256406 | -0.3160999 | -0.3160999 | 0.6556456 | -0.3160999 | -0.3160999 | 0.2406402 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0473878 | -0.3160999 | -0.2803072 | -0.3160999 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2695355 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2747940 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1328346 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0580071 | 0.4616578 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.8882813 | -0.3160999 | -0.3160999 | 0.3940434 | 0.2450862 | 0.6132755 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2733452 | -0.7209945 | -0.3160999 | 0.2839103 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3666922 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2436837 | -0.3160999 | -0.3160999 | 0.2711011 | -0.3160999 | 1.6494093 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2623298 | 0.0984878 | -0.0289935 | 0.4097634 | 0.8531295 | -0.3160999 | 0.8003601 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7037221 | 0.1617823 | 0.3448512 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7452184 | -0.3160999 | 0.7892197 | -0.3160999 | 0.2766619 | -0.0011908 | 3.3749529 | 1.2042692 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0028704 | 0.7498819 | 0.3454073 | -0.3160999 | 0.7744992 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6049995 | -0.3160999 | -0.3160999 | 1.0523151 | -0.3160999 | 0.1769405 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1775506 | -0.3160999 | -0.3160999 | 2.1211860 | -0.3160999 | -0.3160999 | 0.3549869 | 0.2971141 | 0.2682066 | -0.3160999 | 0.6960421 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.9548979 | 0.1656928 | -0.3160999 | 0.2711011 | -0.3160999 | 0.7070950 | -0.3160999 | -0.3160999 | 0.3221213 | -0.3160999 | 0.1989887 | -0.3160999 | 1.0306016 | -0.3160999 | 0.5169146 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0241771 | -0.3160999 | 0.2358579 | -0.3160999 | -0.0058963 | 0.8233290 | 0.2684335 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1467150 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2252176 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3576270 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.3207294 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7777816 | 1.7530250 | -0.3160999 | -0.3160999 | -0.3160999 | 2.3858439 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0193477 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1507561 | -0.1429387 | -0.0354656 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6013160 | -0.3160999 | -0.3160999 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8745383 | -0.3160999 | -0.1375902 | -0.3160999 | -0.3160999 | 0.9791229 | -0.3160999 | 2.8471525 | -0.3160999 | 2.0686174 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7287304 | 0.7604351 | -0.3160999 | -0.3160999 | 0.4163459 | -0.3160999 | -0.0815435 | -0.0063567 | -0.3160999 | -0.3031779 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0925364 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2737674 | -0.3160999 | 0.0074923 | 0.5647146 | -0.3017248 | 0.5594532 | -0.3160999 | -0.3160999 | -0.3160999 | 1.4537745 | 0.4734888 | -0.3160999 | -0.3160999 | 0.7988475 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1436623 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.0980634 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5183010 | 0.3531601 | -0.3160999 | -0.3160999 | 0.9506706 | -0.3160999 | -0.3160999 | 0.2307375 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3131823 | -0.3160999 | 0.3605653 | 0.5186346 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4462961 | 0.3125311 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0910415 | -0.3160999 | -0.1318589 | -0.3160999 | -0.3160999 | 0.7149435 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7601908 | 0.2733114 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0995997 | -0.3160999 | -0.3160999 | -0.0061250 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.9871452 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.2329896 | 0.9261667 | -0.3160999 | 0.9052371 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3887833 | 0.7912356 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4564946 | 0.1436086 | -0.3160999 | -0.3160999 | 0.1052468 | 0.2715357 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2871429 | 0.7492437 | -0.3160999 | 0.1272228 | 2.1335289 | -0.3160999 | -0.3160999 | 4.7649504 | 2.0628798 | -0.3160999 | -0.3160999 | 1.7864409 | -0.3160999 | 0.4364076 | -0.2631006 | -0.3160999 | 0.0629426 | -0.3160999 | 1.1776027 | -0.3160999 | 1.2200033 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1424720 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2711011 | -0.3160999 | -0.3160999 | 1.6331015 | -0.3160999 | -0.1150464 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.3891442 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2508867 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1314751 | -0.3160999 | -0.3160999 | -0.1242041 | -0.5571057 | -0.3160999 | 0.4130476 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5055846 | 1.4785091 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1464829 | 5.6093983 | -0.2981095 | -0.2924035 | 0.1895487 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1844063 | 1.5166655 | 0.0444639 | 0.6106642 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1872153 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1757651 | -0.2022778 | -0.3160999 | 0.3117830 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4057540 | -0.3160999 | 0.8847462 | 1.0307273 | 1.6048548 | 0.2823877 | 9.8578446 | -0.3160999 | -0.3160999 | 1.8903895 | 1.6005870 | -0.3160999 | 0.0231415 | 1.0918737 | -0.3160999 | -0.3160999 | -0.2131032 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3453233 | -0.3160999 | -0.3160999 | -0.0254642 | 3.3125499 | 0.3033062 | 0.6114834 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0275774 | -0.2466783 | 0.9318162 | -0.3160999 | -0.3160999 | 0.1198086 | -0.3160999 | 1.9002727 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0481561 | -0.3160999 | -0.1311168 | 1.5752528 | -0.3160999 | -0.3160999 | 0.5064214 | 0.3020067 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2416019 | -0.3160999 | 0.2234902 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.3344535 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0044342 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3530685 | -0.3160999 | -0.3160999 | 0.0284345 | 0.4301087 | -0.3160999 | 0.0203378 | -0.3160999 | -0.3160999 | 0.5627269 | 0.2213807 | -0.3160999 | 0.3344272 | -0.3160999 | -0.0949818 | -0.3160999 | -0.0329788 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2261125 | -0.3160999 | 2.3653330 | -0.3118925 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1733734 | 2.5779497 | -0.3160999 | 0.0662015 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1935342 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2517654 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0321904 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5313181 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8163554 | 0.6662087 | -0.2976437 | 3.3137348 | -0.3160999 | -0.1912710 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1937166 | 4.5602193 | -0.1468258 | -0.2745351 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3087447 | -0.2616873 | -0.2403536 | -0.3160999 | 5.1400492 | -0.3160999 | 1.5570884 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2061297 | -0.3160999 | 2.1106387 | -0.3160999 | 0.0517689 | 0.0662280 | 0.2225003 | -0.3160999 | 0.7618908 | 0.8645435 | 0.5925426 | 0.3533251 | 0.0479460 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1275737 | 0.9010762 | -0.3160999 | -0.1165166 | 0.2569592 | -0.3160999 | -0.2662535 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0076065 | -0.3160999 | 0.1754448 | -0.3160999 | 2.4008927 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7126188 | -0.3160999 | -0.3160999 | -0.2458126 | -0.3160999 | -0.3160999 | -0.3072452 | -0.3160999 | -0.3160999 | 1.0022891 | 1.1446501 | -0.3160999 | -0.3160999 | 0.3553022 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 4.3984014 | -0.3160999 | -0.3160999 | 0.0811384 | -0.3160999 | 0.4481499 | -0.0475213 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8330179 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1399039 | -0.3160999 | 0.2330281 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7700681 | 1.3144094 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3490527 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 4.0808953 | -0.3160999 | 0.8663627 | -0.3160999 | 0.6829839 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1911457 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1541536 | 0.5683928 | -0.3160999 | 0.3373075 | -0.3160999 | 0.3046908 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0320684 | 0.0761128 | 1.0285963 | 0.2993291 | -0.2962087 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3187155 | -0.3160999 | -0.0284989 | 0.4187053 | -0.3160999 | -0.3160999 | 0.0383715 | -0.3160999 | -0.3160999 | 0.0925748 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.4248120 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7375214 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1557922 | 0.4781758 | -0.3160999 | 1.4376852 | -0.3160999 | -0.1965117 | -0.3160999 | -0.3160999 | 0.2711011 | 1.1398415 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0229409 | -0.3160999 | 0.2821787 | -0.3160999 | -0.3160999 | -0.1028003 | -0.3160999 | -0.3160999 | 0.3973405 | -0.3160999 | 0.2711258 | -0.3160999 | -0.1158722 | -0.3160999 | 0.5977746 | -0.3160999 | 0.2702301 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2485230 | -0.3160999 | -0.3160999 | -0.0027203 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1390473 | -0.2021687 | -0.3160999 | 0.4794630 | -0.3160999 | 0.9185337 | 0.9074902 | -0.3160999 | -0.3160999 | 0.6051639 | -0.1709441 | 0.2711011 | -0.1035663 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3463251 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3852847 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2104264 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.9548245 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0127265 | 3.6291334 | 0.8245393 | -0.2858737 | -0.3160999 | 3.5268659 | -0.3160999 | -0.3160999 | 0.2855727 | -0.3160999 | -0.3160999 | -0.3197328 | -0.0768698 | -0.3160999 | 1.0671672 | -0.3160999 | 0.1803674 | -0.3160999 | -0.2729786 | -0.3160999 | 0.2668441 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3779236 | -0.3160999 | -0.3160999 | -0.3160999 | 5.8477139 | -0.2998012 | -0.0654184 | -0.3160999 | 1.1701899 | 1.1519026 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1599262 | -0.3160999 | 0.3720263 | 0.9463682 | -0.3160999 | -0.3160999 | 0.1191490 | -0.3160999 | 0.3536029 | -0.3160999 | -0.3160999 | 0.6677073 | -0.3160999 | 0.2109510 | 0.2567792 | -0.3160999 | 2.9283865 | 0.6058615 | -0.3160999 | -0.3160999 | -0.1064112 | -0.3160999 | 0.1122983 | 0.2458490 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2186317 | 0.4791846 | -0.3160999 | 0.4536261 | -0.3046742 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2124673 | -0.3160999 | -0.3160999 | -0.2579773 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1855318 | -0.3160999 | 0.9664746 | -0.3160999 | -0.2560075 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0130311 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 3.9386465 | -0.1203662 | 0.0904095 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0618441 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0438751 | -0.3160999 | 0.5793969 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0677629 | 0.9361239 | -0.3160999 | 0.6796421 | -0.2288225 | 0.4963256 | 0.0318569 | -0.3160999 | -0.3160999 | 3.4804899 | -0.3160999 | 0.3079691 | -0.2222210 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.6853511 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0286029 | -0.3160999 | 0.1811908 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4925305 | -0.3160999 | -0.3160999 | -0.1105522 | 0.2205942 | 0.7020274 | -0.3160999 | 0.0879375 | 1.2356140 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2659488 | 0.4416319 | 0.4041550 | -0.3160999 | 0.4935223 | -0.3160999 | -0.3160999 | 1.2270491 | 0.7873219 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3727415 | -0.0365324 | 0.9673278 | 0.0738422 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.3085013 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 7.3197916 | -0.1512572 | 0.1554674 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7347791 | -0.0560219 | 1.3508135 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1262656 | -0.3956051 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2087434 | -0.3160999 | 0.0590609 | -0.3016156 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.9390826 | -0.3160999 | -0.0754800 | -0.3160999 | -0.3160999 | 0.3390168 | 0.1263503 | -0.3160999 | -0.3160999 | 0.6897655 | 0.2696548 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2286296 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8021311 | -0.0893680 | 0.5087749 | -0.1977884 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3453656 | 0.2091323 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7264315 | 0.5563816 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5605390 | -0.3160999 | -0.3160999 | 19.3863260 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0367655 | -0.3160999 | -0.3160999 | -0.0232453 | -0.3160999 | -0.3160999 | -0.2050906 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2624056 | 0.5319112 | -0.1500172 | 1.4455032 | -0.2847901 | 0.8221000 | -0.3160999 | 0.6311640 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.3286584 | 0.2532580 | 0.3278641 | -0.3160999 | -0.3160999 | 0.5714779 | -0.3160999 | -0.3160999 | 0.2969897 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6804472 | 0.1590869 | 0.5078759 | 0.3576099 | -0.0979252 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0363186 | -0.3160999 | 0.2272178 | 0.0654028 | -0.3160999 | -0.3160999 | -0.2761888 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4803925 | -0.3160999 | 0.5605243 | 2.4017553 | 0.1682009 | 25.3897634 | -0.3160999 | 2.5882116 | 3.4153664 | 1.2814815 | 0.7295936 | -0.3160999 | 0.5804128 | -0.1606273 | -0.3160999 | -0.0273535 | -0.3160999 | 2.2014828 | -0.2368151 | 0.4990520 | -0.3160999 | -0.3160999 | 5.9454241 | -0.3160999 | 0.2132638 | 4.8635662 | 0.5242664 | 0.4480207 | 2.0134263 | 0.6876069 | -0.3160999 | -0.3160999 | 0.1732343 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2688160 | -0.3160999 | -0.3160999 | -0.0985516 | -0.0246772 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4147769 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2974436 | -0.3160999 | -0.3160999 | -0.3160999 | 6.8969775 | -0.3160999 | -0.3160999 | -0.0960735 | -0.3160999 | -0.3160999 | 1.1651558 | -0.3160999 | -0.3160999 | 0.5735191 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6302480 | -0.3160999 | 0.2259596 | 0.3364214 | -0.3160999 | -0.1142734 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3103544 | -0.0897298 | 0.1317949 | -0.3160999 | 0.6309144 | -0.3160999 | 0.1394616 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1215530 | -0.3160999 | 1.3593966 | 0.4377817 | -0.3160999 | 0.5338431 | 0.6483772 | -0.2530411 | -0.3160999 | -0.3160999 | -0.3160999 | -0.6277533 | -0.3160999 | 5.3563341 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3854057 | -0.3160999 | -0.3160999 | 11.3567104 | -0.3160999 | 1.0637890 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 3.3988637 | 5.9526232 | -0.3160999 | 0.3525970 | 0.5910488 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1555552 | 0.3111318 | -0.3160999 | -0.3160999 | 0.4339443 | -0.3160999 | -0.2260248 | -0.3160999 | -0.3160999 | -0.5568351 | 0.0787173 | -0.3160999 | 3.8623702 | 0.4133024 | 2.1337380 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2020973 | -0.0276657 | -0.3160999 | -0.2938765 | -0.3160999 | -0.3047987 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0971278 | 1.1093218 | -0.4628043 | -0.3160999 | -0.3160999 | 4.9278054 | -0.0354639 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1329620 | -0.3160999 | -0.3160999 | 0.4515709 | 0.9412525 | 0.3440110 | 0.1787130 | 0.9282501 | 0.0899153 | -0.3160999 | -0.3160999 | -0.2561434 | -0.3160999 | 0.5991780 | -0.3160999 | -0.3160999 | -0.0180675 | -0.3160999 | -0.3160999 | 1.1442526 | -0.3160999 | 0.2774687 | 0.5805913 | 2.9048098 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.8379777 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 3.3761631 | -0.3160999 | -0.3160999 | 0.2212881 | -0.3160999 | -0.3160999 | -0.1725282 | -0.3160999 | 0.1394874 | -0.3160999 | 0.7196387 | -0.3160999 | -0.3160999 | 0.9010580 | -0.3160999 | -0.3160999 | -0.2125686 | -0.3160999 | -0.1977612 | -0.3563011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1877524 | -0.3160999 | 0.8081798 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 4.6903706 | -0.3160999 | 1.4020409 | 3.2160974 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2776632 | -0.2005178 | -0.3160999 | -0.3160999 | -0.1006700 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0102325 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0127108 | -0.3160999 | -0.3160999 | 1.2617257 | -0.3160999 | 0.3101218 | -0.3160999 | 0.2500367 | 0.2389058 | -0.3160999 | -0.3160999 | 0.5687357 | -0.3160999 | -0.3160999 | 1.7460309 | -0.3160999 | 0.6398704 | -0.3160999 | 0.4498804 | 0.2296294 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.7841590 | 2.8779900 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3027469 | 0.2463976 | 1.8492150 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2934060 | -0.3160999 | -0.3160999 | 0.2235197 | -0.1954285 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1123605 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1757813 | 0.8361347 | -0.3160999 | 0.3184965 | 0.8528177 | -0.3160999 | 0.2732403 | 0.6796286 | 0.1461760 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0770185 | -0.3160999 | -0.3160999 | 0.2155224 | -0.3160999 | -0.3160999 | -0.2404777 | 0.6527847 | 2.4132950 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1292148 | -0.0157912 | -0.0684427 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3940193 | -0.1606014 | -0.2762204 | 0.0878583 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2899943 | -0.3160999 | -0.3160999 | 0.2095457 | -0.3160999 | -0.3160999 | -0.3160999 | 1.5192861 | -0.3160999 | 0.0213013 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1864782 | 0.4958259 | -0.3160999 | 6.0441385 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2009087 | -0.1061628 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0192167 | 0.1945874 | -0.3160999 | 0.4281199 | -0.3160999 | -0.2811238 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5648637 | 0.1345103 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8658999 | 0.0941793 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0546213 | -0.3160999 | 0.2903960 | -0.3160999 | 0.3806229 | 1.1099278 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1994926 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7396230 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3365042 | -0.3160999 | 0.5592389 | 0.2475907 | -0.3160999 | -0.3160999 | -0.2848468 | -0.3160999 | -0.3160999 | 0.6533966 | -0.3160999 | -0.3160999 | 1.7355082 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1416003 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1137393 | -0.3160999 | -0.3160999 | -0.1324900 | 0.3581578 | -0.0574075 | -0.3160999 | 0.2826907 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6884249 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2780833 | -0.3160999 | 0.2942850 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2633237 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0500386 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0125130 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1028684 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4142596 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1489324 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0215106 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0643707 | -0.3160999 | -0.3160999 | -0.2205940 | -0.3160999 | 1.0946617 | 0.0104555 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1263328 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6129373 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3706851 | -0.3160999 | -0.2604948 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6625687 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4614829 | 0.2099573 | 2.1886677 | 0.2848293 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.5924195 | 0.0728537 | -0.3160999 | -0.3160999 | 0.1819546 | 0.1236099 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2248251 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 3.0577962 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2891031 | -0.3160999 | -0.0284817 | -0.1222760 | 0.5638937 | 0.1815281 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2711235 | 1.8772139 | -0.3160999 | -0.3160999 | 0.2559210 | -0.3160999 | 0.2711011 | 0.0762125 | -0.3160999 | 0.1466159 | 0.5604897 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0661422 | 0.7263663 | 0.2711011 | -0.3160999 | -0.1483557 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1502748 | 1.1500759 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3666059 | -0.3160999 | -0.3160999 | 0.9808909 | -0.2205476 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2405821 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1060067 | 2.9123348 | -0.2858763 | -0.3160999 | 0.2651759 | 1.7872036 | 3.9930700 | -0.3160999 | 0.1220585 | 0.0353769 | -0.2910590 | -0.3384080 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2447281 | -0.3160999 | -0.3160999 | 0.8752259 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2042381 | 2.7360805 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0507924 | -0.3160999 | -0.3160999 | -0.2964447 | -0.2109373 | -0.3160999 | -0.2675599 | 1.5361711 | -0.1775708 | -0.3160999 | -0.3160999 | -0.1161668 | -0.3160999 | -0.3160999 | 1.2179680 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 3.3051488 | -0.3160999 | -0.2791640 | -0.3160999 | 3.0425672 | -0.3160999 | 0.4160670 | -0.3160999 | 0.4456261 | -0.3160999 | -0.3160999 | -0.0680165 | -0.3160999 | -0.1011443 | -0.0805333 | 0.5586635 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2415808 | -0.3160999 | 1.6876390 | -0.1821077 | -0.0398332 | -0.0945307 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3045393 | -0.3160999 | 0.2635564 | -0.3160999 | -0.3160999 | -0.2259885 | -0.1176302 | -0.2577367 | 15.1283788 | -0.3160999 | -0.3160999 | -0.2148550 | 1.8040921 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2777713 | -0.3160999 | 4.0807914 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3312082 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5493369 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.9426845 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1922347 | 1.8193928 | 1.9307942 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2672970 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4758476 | -0.3160999 | 0.1349850 | -0.3160999 | -0.2909379 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6781624 | -0.3160999 | -0.3160999 | -0.2558550 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2974042 | -0.3160999 | 1.0435817 | -0.2812414 | -0.3160999 | 5.9784953 | -0.3160999 | -0.3160999 | 0.3331483 | -0.0408494 | -0.2338230 | -0.3160999 | -0.3160999 | -0.0375100 | -0.2038868 | -0.3160999 | -0.2863083 | -0.3160999 | 0.2456717 | -0.3160999 | -0.3160999 | -0.1862162 | -0.3160999 | 0.3934891 | 2.0978523 | -0.3160999 | -0.1135528 | -0.0493512 | -0.3076316 | 1.1184803 | -0.3160999 | 0.7729531 | -0.3160999 | -0.3160999 | -0.3160999 | 1.3053782 | 0.2334918 | -0.3160999 | 0.7195965 | -0.3160999 | -0.3160999 | 0.5040620 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6561858 | -0.3160999 | -0.3160999 | -0.3160999 | 3.2066264 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1416914 | -0.3160999 | -0.0551217 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2737245 | 0.1047948 | -0.2265346 | -0.3160999 | -0.3160999 | -0.0935183 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6552886 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2999898 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2084124 | -0.3160999 | -0.3160999 | 1.2247361 | -0.3160999 | -0.3160999 | -0.2827934 | 0.2190485 | -0.3160999 | 0.7619977 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4783485 | -0.3160999 | -0.1498768 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3103080 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1615450 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0582266 | -0.3160999 | 4.2952513 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1508514 | -0.3160999 | -0.0887962 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.1820358 | -0.3160999 | -0.3160999 | 1.3398128 | 0.5577721 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2671268 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2174772 | 0.2224758 | -0.0078408 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2437958 | 0.2711011 | -0.3160999 | -0.3160999 | 0.2079251 | -0.3160999 | 0.2428192 | -0.3160999 | 0.2711011 | -0.3160999 | 0.0823555 | -0.3160999 | -0.2423307 | -0.3160999 | -0.3160999 | -0.2612909 | 0.2681971 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2539662 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3123138 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6645505 | 0.0811406 | -0.3160999 | -0.3160999 | 0.7794399 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0223513 | -0.3160999 | -0.3160999 | 0.5753987 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0368238 | 0.4167293 | -0.3160999 | -0.1702317 | 0.9203916 | 0.0328008 | -0.3160999 | -0.2867093 | 0.8175158 | 1.5140342 | -0.3160999 | 0.0283229 | -0.3160999 | 0.0065380 | -0.3160999 | -0.3160999 | -0.0082153 | -0.3160999 | -0.3160999 | -0.3160999 | 3.0320486 | 0.7625185 | 0.3301395 | 1.6103669 | -0.3160999 | -0.3160999 | 0.0690399 | -0.2102079 | -0.3160999 | 3.3305170 | -0.3160999 | -0.3160999 | 1.3828664 | 1.0754990 | -0.3160999 | 0.1551834 | -0.3160999 | -0.0617633 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0518926 | -0.3160999 | 0.1077020 | -0.3160999 | 0.5169229 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1899068 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.3960947 | -0.2023902 | -0.3160999 | -0.3160999 | 0.2326478 | -0.3160999 | 0.4069360 | 0.5174907 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5237326 | 0.5439934 | 0.3581690 | -0.3160999 | 1.7282205 | 0.2977824 | -0.3160999 | -0.2336844 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1829492 | -0.3160999 | -0.3160999 | -0.3160999 | 2.1086868 | 0.0546745 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2256598 | -0.3160999 | -0.3160999 | 0.2814717 | -0.3160999 | 0.1349554 | 0.4403865 | -0.3160999 | -0.3160999 | 3.4474188 | -0.3160999 | 1.3961965 | -0.3160999 | 0.1309520 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1196958 | -0.3160999 | 0.5034495 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1708817 | -0.3160999 | -0.3160999 | 2.1136169 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0478867 | -0.3160999 | -0.3160999 | 0.6247306 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6923098 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0269453 | 0.3596487 | 0.5080403 | -0.3160999 | 0.9551187 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2616706 | -0.3160999 | 0.6433038 | -0.2000551 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7158877 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.9708583 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2389774 | 0.0309216 | -0.3160999 | -0.3160999 | 1.1139859 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1973987 | -0.3160999 | 0.1987790 | -0.3160999 | 0.7907118 | 0.7392824 | -0.3160999 | -0.1691882 | -0.1521819 | -0.3160999 | -0.3160999 | 0.8527478 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6745769 | 0.2776144 | 1.2400333 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0146839 | -0.3160999 | -0.1093208 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.3373229 | -0.1683290 | 0.5011313 | -0.1995267 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1254926 | -0.2112426 | 1.7266397 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0531874 | -0.3160999 | -0.0451771 | -0.3160999 | -0.2904983 | -0.3160999 | -0.1182469 | -0.3160999 | -0.3160999 | -0.0141538 | -0.3160999 | -0.3160999 | 0.3453691 | 0.2475702 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0410156 | -0.3160999 | -0.3113565 | 1.6402801 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5792114 | 21.3660448 | 0.6214024 | -0.3160999 | 0.0902249 | 0.3115840 | -0.0043106 | -0.0063900 | -0.0101393 | -0.3160999 | -0.3160999 | -0.0392077 | -0.3160999 | -0.1460199 | -0.3160999 | -0.3160999 | 0.1258998 | 1.0116221 | -0.2177675 | 1.1269613 | -0.3160999 | 0.9819790 | 0.1872332 | -0.3160999 | 0.5076005 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2398245 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1169078 | 1.2727797 | -0.3160999 | -0.3160999 | 0.5545296 | -0.3160999 | -0.3160999 | -0.0951102 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0310729 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1265778 | 3.1118951 | -0.2177257 | -0.3160999 | -0.2155779 | -0.3160999 | -0.3160999 | -0.3160999 | 11.3514021 | -0.3160999 | -0.3160999 | -0.3160999 | 1.6789890 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2245447 | -0.3160999 | -0.3160999 | 0.1113338 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3156709 | -0.3160999 | -0.3160999 | 0.7990647 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8541753 | -0.3160999 | 0.0269428 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0831845 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.0897310 | -0.1319195 | 0.0069184 | -0.2543185 | 0.1338865 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2958241 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7924740 | -3.4212986 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0227650 | -0.3160999 | -0.3160999 | 0.1246481 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2085438 | -0.3160999 | -0.3160999 | -0.0691137 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.4858515 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0426412 | -0.3160999 | -0.3160999 | 0.4415914 | -0.3160999 | 0.1371138 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0163043 | -0.3160999 | 0.2530023 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2495034 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4861283 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4512021 | -0.3160999 | -0.1418709 | 0.1522479 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.5071927 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4105103 | -0.2739162 | -0.2442944 | 3.4757647 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6163518 | 0.0775432 | 0.7328784 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3287936 | 0.7047749 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1458598 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3980634 | -0.3160999 | -0.1905918 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1546493 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1938678 | -0.0040607 | -0.3160999 | 0.2990631 | -0.3160999 | -0.3160999 | -0.3160999 | 0.9980912 | 0.1418379 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.6231559 | 0.7744164 | -0.3160999 | -0.3160999 | -0.3160999 | 2.0177153 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1087671 | 0.6180377 | -0.3160999 | 0.4044245 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8647361 | 1.2376252 | -0.3160999 | -0.0058846 | -0.3160999 | -0.3160999 | 0.4124774 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.5547384 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1279614 | -0.3160999 | -0.3160999 | 0.2227076 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1386503 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1614393 | -0.3160999 | -0.3160999 | -0.0787923 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2150848 | 0.2952245 | -0.3160999 | 0.2633543 | -0.3160999 | -0.3160999 | -0.1461176 | 0.7842802 | -0.3160999 | 1.0213685 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1422799 | -0.3160999 | 0.3105975 | -0.3160999 | 0.4617594 | -0.3160999 | 1.4455032 | -0.3160999 | 0.9455403 | -0.2595357 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0834613 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1099476 | -0.3160999 | 1.1717072 | 0.1428237 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1237916 | 0.7998845 | -0.3160999 | -0.3160999 | -0.3160999 | 1.9208112 | 0.8135310 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1799369 | -0.3160999 | 0.9682414 | -0.3160999 | -0.2986458 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0978819 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2398154 | -0.3160999 | 1.1374951 | -0.0628323 | 0.0902676 | -0.3160999 | -0.4599766 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8312222 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6603543 | 0.1053977 | -0.3160999 | -0.3160999 | -0.3160999 | 1.0468266 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -1.6381624 | -0.3160999 | -0.3160999 | 0.3072809 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3183033 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7298519 | -0.3160999 | -0.3160999 | 0.4409514 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2711011 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4657095 | -0.3160999 | -0.3160999 | -0.0929421 | 2.0867343 | -0.3160999 | 0.4050716 | -0.3160999 | 0.6167353 | -0.0224994 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8098968 | -0.0061786 | 5.0874759 | 1.4650840 | -0.1996150 | -0.3160999 | 0.1990557 | 0.7892197 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2027184 | -0.3160999 | 0.2754429 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0408063 | 1.1119636 | -0.3160999 | -0.2625404 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2606933 | -0.3160999 | 0.0642372 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0813099 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2134384 | 4.6577892 | -0.3160999 | -0.3160999 | 0.2707609 | -0.3160999 | 0.5167755 | -0.3160999 | 0.9625333 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4850097 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.7237659 | -0.3160999 | 0.3296727 | 0.0424065 | -0.3160999 | 0.4106107 | -0.3160999 | -0.3160999 | 0.5602935 | 0.1727095 | -0.3160999 | 1.1562820 | -0.3160999 | 0.8745418 | -0.3160999 | -0.3160999 | 0.3118229 | -0.3160999 | -0.0008320 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1194230 | -0.3160999 | -0.3160999 | -0.1501903 | 0.2711123 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2769549 | -0.3160999 | -0.3160999 | -0.2573767 | -0.3160999 | -0.3160999 | -0.0033787 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3164207 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2562655 | 0.4434840 | 0.2388713 | -0.3160999 | -0.1793709 | -0.3160999 | 0.9756126 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2814030 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.4817910 | 1.0678994 | 0.2711011 | -0.3160999 | -0.0109074 | 0.2158247 | 0.0963610 | 1.0540356 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5589071 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1898201 | 0.0812692 | 0.4797507 | -0.3160999 | -0.3160999 | 1.6647188 | 0.4950590 | 0.8621794 | -0.3160999 | -0.0986531 | -0.3160999 | 0.2177304 | -0.3160999 | 0.1266232 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2729603 | -0.3160999 | 0.1132421 | -0.3160999 | 0.3369140 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2473959 | -0.3160999 | -0.3160999 | 0.2785445 | 0.1639316 | -0.3160999 | 0.5647016 | 0.5746588 | 1.2802307 | -0.3160999 | 0.2095494 | -0.3160999 | 0.2629042 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1095340 | 0.7039822 | 0.1721683 | -0.3160999 | -0.3160999 | 0.0733493 | 0.2944160 | -0.3160999 | 0.4029888 | -0.0926214 | -0.1920339 | 0.9370969 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1746887 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6591899 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0846414 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3622007 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3066954 | -0.3160999 | -0.3160999 | 2.2724489 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1071043 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2643018 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4823902 | -0.1802233 | -0.3160999 | -0.3160999 | 0.7008201 | -0.3160999 | -0.3160999 | 1.0022774 | -0.3160999 | 2.0255333 | -0.3160999 | 0.2354994 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0291606 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.7046584 | -0.3160999 | 0.4472297 | -0.3160999 | 1.5993663 | -0.0038507 | 2.0656591 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2203785 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2718819 | -0.3160999 | -0.3160999 | -0.3160999 | 3.9942039 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0855277 | 0.6922992 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2517374 | -0.3160999 | -0.3160999 | 0.0627875 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1481654 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2778840 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0683551 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3012763 | -0.3160999 | -0.3160999 | 0.4490154 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.4251267 | -0.3160999 | -0.3160999 | -0.3160999 | 1.5678835 | -0.3160999 | 0.0182988 | -0.3160999 | 0.2609854 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4640619 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6420877 | 1.1041767 | 0.1008157 | 0.2095275 | 0.1378139 | -0.3160999 | 1.2597439 | -0.3160999 | -0.3160999 | 0.7087086 | 1.0929553 | 1.6366735 | 5.0019941 | -0.3160999 | -0.3160999 | -0.3160999 | 1.7778108 | -0.3160999 | 1.4455032 | -0.2538084 | 1.2243691 | -0.3160999 | 11.0367974 | -0.3072991 | -0.3160999 | 3.5068012 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0710692 | 0.9923155 | -0.3160999 | -0.3160999 | 0.4221915 | -0.3160999 | -0.0556323 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2359207 | 1.2878373 | -0.3160999 | 0.2591174 | 1.2630551 | -0.3418788 | -0.3160999 | -0.3160999 | 0.2712180 | -0.3160999 | -0.3160999 | 1.4075165 | 0.9421081 | -0.3160999 | 5.1784545 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1458139 | -0.3160999 | -0.3160999 | -0.0089486 | 1.1447840 | -0.3160999 | -0.3160999 | 0.8296279 | 0.3593792 | -0.3160999 | 1.3282403 | 6.5117795 | 1.1994712 | -0.0274002 | 0.1949045 | -0.0141668 | -0.3160999 | 1.4218595 | -0.0402330 | 0.6492204 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2740481 | 3.0697270 | -0.3160999 | -0.3160999 | 1.1416801 | 3.0877875 | 0.2807312 | 0.9939015 | -0.3160999 | 0.1449693 | 0.9012089 | -0.3160999 | 1.1809298 | 0.0890485 | 0.8499792 | -0.3160999 | -0.3160999 | 0.4526379 | -0.3160999 | 0.2117026 | -0.3160999 | -0.3160999 | 0.1314243 | 0.5328454 | -0.2305396 | -0.3160999 | 6.2515379 | 2.2155139 | -0.1285551 | 1.2193985 | -0.2176978 | -0.3160999 | 0.2731070 | -0.3160999 | -0.3160999 | -0.3160999 | 1.4137092 | -0.3160999 | 1.0804015 | -0.3160999 | 3.5986876 | 2.2252720 | 0.0253260 | -0.3160999 | 0.1139977 | 6.2874159 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8674766 | 0.1652876 | -0.3160999 | -0.3160999 | 1.4383763 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1846931 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.6560746 | -0.3160999 | 0.7901551 | -0.3160999 | -0.1683271 | -0.3160999 | 14.7404033 | -0.3160999 | -0.3160999 | -0.3160999 | 2.0683766 | -0.3160999 | 0.4870120 | -0.3160999 | -0.3160999 | 1.4813946 | -0.3160999 | 0.5305917 | -0.3160999 | -0.3160999 | -0.3160999 | 3.2906942 | 1.4841257 | -0.2133620 | -0.1815600 | 0.6551024 | -0.3160999 | 0.7876431 | 0.2600282 | -0.3160999 | 0.0437707 | 2.1920734 | 2.6609834 | -0.3160999 | 4.1818504 | 0.9477481 | -0.3160999 | -0.3160999 | 0.5788608 | -0.3160999 | -0.2750905 | 1.5059843 | 1.3805675 | 1.4912220 | -0.3160999 | -0.3160999 | 1.4068142 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7717458 | -0.3160999 | 0.5852596 | 4.6323164 | -0.3357662 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2374701 | 0.2536559 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4743067 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2574232 | -0.3160999 | -0.3160999 | 0.1296512 | 0.6753914 | 0.4828053 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2275547 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2711011 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2260186 | -0.3160999 | -0.3160999 | 1.4841474 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2715791 | -0.3160999 | 0.2895622 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1152344 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.0912968 | -0.3160999 | 0.6392938 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.1787234 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1182104 | -0.3160999 | 0.2349643 | -0.3160999 | -0.3160999 | 0.7482525 | -0.3160999 | -0.1769794 | -0.3160999 | 0.5519617 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.8638839 | 0.3381025 | -0.3160999 | -0.3160999 | -0.1369808 | 0.7590346 | -0.3160999 | 0.9730260 | -0.3160999 | 0.1481159 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1878880 | -0.3160999 | -0.3160999 | 0.8180313 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1832773 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2197332 | 0.4829227 | -0.3160999 | -0.1148454 | 1.0394466 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1080368 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2111829 | -0.3160999 | -0.0120817 | 0.0744991 | -0.3160999 | 1.6259459 | 0.3080484 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2011238 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2389157 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2787321 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3694896 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0849272 | -0.3160999 | 0.0113438 | 0.6614800 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2243497 | -0.3160999 | 0.2755838 | -0.0597602 | -0.3160999 | -0.3160999 | 0.8236414 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2386316 | -0.3160999 | 0.6629597 | 1.6843783 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2378121 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.5530946 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2407287 | -0.3160999 | 0.1186222 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5407926 | 1.2604697 | -0.3160999 | -0.3160999 | 0.9696079 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2625143 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0637306 | -0.3160999 | -0.3160999 | 0.7232171 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4994572 | -0.3160999 | -0.3160999 | 0.1386995 | 0.3709112 | -0.3160999 | -0.3160999 | 0.4746949 | -0.3160999 | -0.3160999 | 0.5022199 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2061169 | 0.3093062 | -0.0738888 | 0.8292756 | -0.3160999 | -0.3160999 | 0.2610394 | 1.7492164 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2683989 | -0.3160999 | -0.3160999 | -0.2243791 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5225418 | -0.3160999 | 0.2480491 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1017510 | -0.3160999 | -0.3160999 | 0.1742184 | -0.2110802 | -0.3160999 | -0.3160999 | 0.3963975 | -0.1790659 | 3.2289917 | -0.3160999 | 2.6515254 | -0.3160999 | -0.3160999 | 1.2250468 | 0.6694442 | -0.3160999 | -0.3160999 | 0.5920405 | -0.3160999 | 0.1481212 | -0.0383630 | 1.9450644 | -0.3160999 | -0.3160999 | 0.2134511 | -0.3160999 | -0.1771773 | 0.1735601 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1095651 | 0.2888880 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1829020 | 1.3131257 | 2.1152018 | -0.3160999 | 2.5116459 | -0.3160999 | -0.3160999 | 1.1867102 | -0.2071883 | 0.1629486 | 0.8280143 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0023284 | -0.3160999 | 1.2819154 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2501428 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1171615 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0189419 | -0.3160999 | 1.4889408 | 0.0759695 | -0.3160999 | 0.1601730 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0258131 | -0.3160999 | -0.0629354 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3533240 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0842408 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0035661 | -0.3160999 | -0.3160999 | -0.0088232 | 0.4366331 | -0.3160999 | -0.3160999 | -0.3160999 | 1.1264281 | 0.0274428 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0738582 | -0.1491764 | -0.3160999 | -0.3160999 | 2.4744320 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1056799 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2436713 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0594275 | -0.3160999 | 0.6011058 | 0.1807625 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8145492 | -0.3160999 | -0.3160999 | 0.1190957 | -0.0176910 | 0.2222121 | -0.3160999 | 0.3793240 | 2.1266933 | -0.3160999 | -0.3160999 | -0.1373009 | -0.3160999 | 0.4768705 | 0.3541889 | -0.3160999 | 0.3403797 | -0.3160999 | 0.3544760 | -0.3160999 | -0.1001129 | -0.2788620 | 0.9732520 | -0.3160999 | -0.3160999 | 1.2737944 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1147548 | -0.3160999 | 0.5968626 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1824436 | 0.4743737 | -0.3160999 | 0.2810495 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.9321703 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1681054 | -0.3160999 | -0.3307480 | -0.3160999 | 0.3902577 | -0.3160999 | -0.3160999 | -0.3160999 | 1.2142517 | 0.2224625 | -0.3160999 | 0.8100794 | -0.3160999 | -0.3160999 | 0.3380356 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4071638 | -0.3160999 | 0.1824477 | -0.3160999 | 0.1868953 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4442139 | -0.3160999 | -0.3160999 | -0.1589766 | -0.8568128 | -0.3160999 | -0.0509385 | 0.5026627 | 0.9684047 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1238545 | -0.3160999 | -0.3160999 | 0.3947974 | -0.3160999 | 0.2591207 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3675695 | -0.3160999 | 0.2809890 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2666861 | 0.2526553 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4255896 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.2651348 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2022352 | -0.0683984 | -0.3160999 | -0.2001019 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1167542 | -0.3160999 | 0.4979604 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.8695889 | -0.3160999 | 1.0770198 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1918848 | -0.3160999 | -0.2493147 | -0.3160999 | 1.5576838 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0845793 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.3472362 | -0.3160999 | -0.3160999 | 0.1439297 | -0.3160999 | -0.2351290 | -0.3160999 | -0.0466152 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1840815 | -0.3160999 | -0.1422723 | -0.3160999 | 1.1389836 | 0.3787063 | 0.2633748 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0930545 | -0.3160999 | 0.7034244 | -0.3160999 | -0.3160999 | 0.1760563 | -0.3160999 | -0.3160999 | -0.2696832 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2853014 | -0.3160999 | -0.2897920 | 0.0024856 | -0.3160999 | 1.6297563 | -0.3160999 | 0.0477357 | 0.5344808 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2778833 | -0.3160999 | 0.2094013 | -0.3160999 | 0.1019562 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.9797049 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4561082 | -0.3160999 | 2.5704646 | -0.3160999 | 0.3323914 | -0.3160999 | -0.3160999 | 0.8645523 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5750129 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0835987 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1054003 | 0.5016204 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2344011 | 1.3740625 | -0.1966851 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6594166 | -0.3160999 | 0.2113073 | -0.3160999 | -0.3160999 | 0.4255896 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0301093 | -0.3160999 | -0.3160999 | -0.2012772 | 0.9319172 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1147011 | -0.3160999 | -0.1084296 | -0.3160999 | -0.3160999 | 0.1940413 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6017693 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7672731 | -0.3160999 | -0.3160999 | 0.3399640 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0924220 | -0.3160999 | -0.3160999 | -0.1303667 | 0.2412285 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1777545 | -0.3160999 | 1.1106459 | -0.3160999 | 1.7935319 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.9454827 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0763768 | -0.3160999 | -0.3160999 | 0.2552309 | -0.3160999 | 0.4146260 | -0.3160999 | 0.3345112 | 0.3347907 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3558325 | -0.3160999 | -0.3160999 | -0.0960727 | -0.3160999 | 0.9999937 | -0.4541273 | -0.3160999 | 0.3689682 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4790484 | -0.3160999 | -0.3160999 | -0.2938363 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3022067 | -0.3160999 | -0.3160999 | -0.1724128 | -0.3160999 | 0.2861417 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3323568 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4458610 | -0.0179986 | 0.1780585 | -0.3160999 | -0.3160999 | -0.1035070 | -0.3160999 | 0.9240076 | -0.2113515 | -0.2665243 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5895520 | -0.3160999 | -0.3160999 | 1.1879591 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2104326 | -0.3160999 | 0.4631399 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6339450 | -0.3160999 | -0.3160999 | -0.3160999 | 0.3168981 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1566191 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.8014652 | 0.7972068 | -0.3160999 | -0.3160999 | -0.1063228 | -0.2855562 | -0.3160999 | -0.3160999 | 0.6692346 | -0.3160999 | 0.6163219 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4215297 | 0.7689542 | -0.3160999 | -0.2545068 | -0.3160999 | 0.5348824 | 0.1905592 | 0.8762952 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1952682 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1076534 | 0.8342345 | 0.1877083 | -0.3160999 | -0.3160999 | 2.9967496 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2137266 | 0.0541597 | 0.5936448 | -0.3160999 | -0.1668183 | -0.3160999 | 0.0904014 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0385210 | -0.3160999 | 0.7383658 | -0.3160999 | -0.3160999 | 0.9420893 | -0.0726518 | 0.1634326 | -0.3160999 | 1.1329560 | -0.3160999 | -0.3160999 | 2.3219083 | 0.4750231 | 0.7964417 | -0.1147976 | -0.1947636 | -0.3160999 | -0.2106815 | 2.6281600 | -0.3160999 | 2.1865185 | -0.0862214 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6303836 | 0.7013122 | -0.3160999 | -0.3160999 | 0.7536770 | -0.3160999 | 0.8741384 | 2.1245776 | 0.2517867 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5273856 | -0.3160999 | 1.3053095 | -0.3160999 | 0.8344929 | -0.3160999 | -0.2096006 | -0.3160999 | -0.3160999 | 0.5901392 | -0.3160999 | -0.0262372 | 0.3461889 | 0.6303425 | 0.5202429 | 1.8861640 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 4.2670521 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.2196615 | 1.7962829 | 3.3928713 | 3.2836508 | -0.3953660 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1830953 | -0.3160999 | 0.6751976 | -0.0030325 | 0.1041237 | 0.4026847 | 3.7513076 | -0.2477106 | -0.3160999 | 0.5004442 | -0.3160999 | -0.3160999 | -0.0228417 | -0.2249616 | -0.3160999 | -0.3160999 | -0.3148430 | 0.2390163 | -0.3160999 | -0.3160999 | -0.1600901 | 0.1889521 | 0.9541069 | -0.3160999 | -0.3160999 | 0.0594980 | -0.3160999 | 1.0558501 | -0.7650918 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0728043 | 0.1540434 | -0.3160999 | 0.2006362 | -0.3107055 | -0.3160999 | 0.2240408 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1333447 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0003271 | -0.3160999 | 0.5082734 | -0.3160999 | -0.3160999 | -0.3160999 | 0.4454170 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1092368 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2383249 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1773613 | -0.3160999 | 0.1859906 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6298645 | 0.0653395 | -0.3160999 | -0.3160999 | 0.4312778 | -0.1347519 | -0.3160999 | -0.3160999 | -0.3160999 | 0.7970154 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8652164 | -0.3160999 | -0.3160999 | 8.3522553 | -0.1518223 | -0.1130896 | 0.3055493 | -0.3160999 | 1.6236247 | -0.3160999 | -0.2706291 | 2.4602311 | -0.2400024 | -0.3160999 | -0.3160999 | 7.4089815 | -0.3160999 | -0.3160999 | -0.1717447 | 0.1524901 | 0.4586649 | -0.3160999 | 0.7859014 | 7.1541891 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 2.4397378 | -0.3160999 | -0.3160999 | 2.2274400 | -0.3160999 | -0.3160999 | 3.8618329 | -0.1120649 | 13.3311562 | 0.7168413 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.1285282 | -0.3160999 | -0.1115028 | -0.1350925 | -0.3160999 | -0.3160999 | -0.3160999 | 2.6795425 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5315201 | -0.0225950 | -0.1859577 | -0.3160999 | -0.3160999 | 0.8365875 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6884079 | 5.2893086 | -0.3160999 | -0.1771854 | -0.3160999 | -0.3160999 | 1.3806368 | -0.3160999 | -0.3160999 | 2.7618211 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2406839 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1040004 | 0.2272581 | -0.3160999 | -0.3160999 | 0.7713265 | -0.3160999 | -0.0263149 | 0.5805091 | -0.3160999 | 0.2044568 | 3.4510107 | -0.3160999 | -0.3160999 | -0.2751481 | 0.0696573 | -0.3160999 | -0.2804279 | -0.3160999 | 2.5929198 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.0930827 | 1.8851969 | 1.0602600 | 0.5281407 | 0.0676295 | 0.4135561 | 1.4694527 | 0.2623834 | -0.3160999 | -0.3160999 | -0.1321721 | -0.3160999 | 0.3446980 | 0.0736522 | 0.3512964 | 1.2731849 | 0.8457272 | 0.0726717 | -0.3160999 | 0.0215550 | 0.4476584 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.6537642 | -0.3160999 | -0.1595644 | 2.5803607 | -0.3160999 | 0.0615389 | -0.3160999 | 1.9743270 | 0.6643103 | -0.3160999 | -0.3160999 | 0.7617998 | -0.1991765 | 1.0198916 | -0.3160999 | -0.3160999 | 2.6641789 | -0.0241962 | 0.1597649 | 0.1515554 | -0.3160999 | -0.3160999 | -0.3160999 | 5.2131610 | -0.3160999 | 2.7685099 | 1.4442835 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 3.1770344 | -0.3160999 | -0.1409171 | 0.0513009 | -0.3160999 | -0.3160999 | -0.3160999 | 0.8560085 | -0.1973388 | -0.2144649 | 1.4485137 | -0.3160999 | -0.3160999 | -0.3160999 | 2.1278988 | 1.4951357 | -0.3160999 | 1.1012953 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.0750401 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.2111392 | -0.3160999 | -0.3160999 | 0.1892165 | -0.0045291 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.5904610 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 1.0620750 | -0.3160999 | -0.3160999 | -0.1970609 | -0.3160999 | -0.3160999 | -0.3160999 | 0.0362207 | -0.3160999 | 0.0519722 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | 0.1776213 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 | -0.3160999 |
#H = 10.0
#MeanShift clustering using multi-core processing
options(mc.cores = 2)
ms_clustering <-
msClustering(model_df_trans, h = 10.0, multi.core = TRUE)
#attach clustering labels to model df
model_ms <- model_df
model_ms[, 'ms_label'] <- ms_clustering[2]
#change labels to factors
model_ms[, 'ms_label'] <- as.factor(model_ms[, 'ms_label'])
#view factor levels of ms_label column
levels(model_ms$ms_label)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14"
## [15] "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28"
## [29] "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42"
## [43] "43" "44" "45" "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56"
## [57] "57" "58" "59" "60" "61" "62" "63" "64" "65" "66" "67" "68" "69" "70"
## [71] "71" "72" "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84"
## [85] "85"
#view number of occurances per factor level
model_ms %>%
group_by(ms_label) %>%
summarise(no_rows = length(ms_label)) #cluster 1 has 5377 data points, cluster 2 has 3 data points,cluster 3 has 2 data points and clusters 4-85 have one point each.
## # A tibble: 85 x 2
## ms_label no_rows
## <fctr> <int>
## 1 1 5377
## 2 2 3
## 3 3 2
## 4 4 1
## 5 5 1
## 6 6 1
## 7 7 1
## 8 8 1
## 9 9 1
## 10 10 1
## # ... with 75 more rows
#plot using principal component anlaysis to reduce high-dimensional data to two dimensions
autoplot(
prcomp(model_ms[, 3:12], center = TRUE, scale. = TRUE),
data = model_ms,
colour = 'ms_label',
frame = TRUE
)
#H = 20.0
#MeanShift clustering using multi-core processing
options(mc.cores = 2)
ms_clustering <-
msClustering(model_df_trans, h = 20.0, multi.core = TRUE)
#attach clustering labels to model df
model_ms <- model_df
model_ms[, 'ms_label'] <- ms_clustering[2]
#change labels to factors
model_ms[, 'ms_label'] <- as.factor(model_ms[, 'ms_label'])
#view factor levels of ms_label column
levels(model_ms$ms_label)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14"
## [15] "15" "16" "17" "18" "19" "20" "21" "22" "23"
#view number of occurances per factor level
model_ms %>%
group_by(ms_label) %>%
summarise(no_rows = length(ms_label)) #cluster 1 has 5449 data points, clusters 2-23 have one point each.
## # A tibble: 23 x 2
## ms_label no_rows
## <fctr> <int>
## 1 1 5449
## 2 2 1
## 3 3 1
## 4 4 1
## 5 5 1
## 6 6 1
## 7 7 1
## 8 8 1
## 9 9 1
## 10 10 1
## # ... with 13 more rows
#plot using principal component anlaysis to reduce high-dimensional data to two dimensions
autoplot(
prcomp(model_ms[, 3:12], center = TRUE, scale. = TRUE),
data = model_ms,
colour = 'ms_label',
frame = TRUE
)
#H = 30.0
#MeanShift clustering using multi-core processing
options(mc.cores = 2)
ms_clustering <-
msClustering(model_df_trans, h = 30.0, multi.core = TRUE)
#attach clustering labels to model df
model_ms <- model_df
model_ms[, 'ms_label'] <- ms_clustering[2]
#change labels to factors
model_ms[, 'ms_label'] <- as.factor(model_ms[, 'ms_label'])
#view factor levels of ms_label column
levels(model_ms$ms_label)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14"
## [15] "15" "16" "17" "18" "19"
#view number of occurances per factor level
model_ms %>%
group_by(ms_label) %>%
summarise(no_rows = length(ms_label)) #cluster 1 has 5453 data points, 2-19 have one point each.
## # A tibble: 19 x 2
## ms_label no_rows
## <fctr> <int>
## 1 1 5453
## 2 2 1
## 3 3 1
## 4 4 1
## 5 5 1
## 6 6 1
## 7 7 1
## 8 8 1
## 9 9 1
## 10 10 1
## 11 11 1
## 12 12 1
## 13 13 1
## 14 14 1
## 15 15 1
## 16 16 1
## 17 17 1
## 18 18 1
## 19 19 1
#plot using principal component anlaysis to reduce high-dimensional data to two dimensions
autoplot(
prcomp(model_ms[, 3:12], center = TRUE, scale. = TRUE),
data = model_ms,
colour = 'ms_label',
frame = TRUE
)
#H = 50.0
#MeanShift clustering using multi-core processing
options(mc.cores = 2)
ms_clustering <-
msClustering(model_df_trans, h = 50.0, multi.core = TRUE)
#attach clustering labels to model df
model_ms <- model_df
model_ms[, 'ms_label'] <- ms_clustering[2]
#change labels to factors
model_ms[, 'ms_label'] <- as.factor(model_ms[, 'ms_label'])
#view factor levels of ms_label column
levels(model_ms$ms_label)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9"
#view number of occurances per factor level
model_ms %>%
group_by(ms_label) %>%
summarise(no_rows = length(ms_label)) #cluster 1 has 5463 data points, 2-9 have one point each.
## # A tibble: 9 x 2
## ms_label no_rows
## <fctr> <int>
## 1 1 5463
## 2 2 1
## 3 3 1
## 4 4 1
## 5 5 1
## 6 6 1
## 7 7 1
## 8 8 1
## 9 9 1
#plot using principal component anlaysis to reduce high-dimensional data to two dimensions
autoplot(
prcomp(model_ms[, 3:12], center = TRUE, scale. = TRUE),
data = model_ms,
colour = 'ms_label',
frame = TRUE
)
#H = 75.0
#MeanShift clustering using multi-core processing
options(mc.cores = 2)
ms_clustering <-
msClustering(model_df_trans, h = 75.0, multi.core = TRUE)
#attach clustering labels to model df
model_ms <- model_df
model_ms[, 'ms_label'] <- ms_clustering[2]
#change labels to factors
model_ms[, 'ms_label'] <- as.factor(model_ms[, 'ms_label'])
#view factor levels of ms_label column
levels(model_ms$ms_label)
## [1] "1" "2" "3" "4"
#view number of occurances per factor level
model_ms %>%
group_by(ms_label) %>%
summarise(no_rows = length(ms_label)) #cluster 1 has 5468 data points, 2-4 have one point each.
## # A tibble: 4 x 2
## ms_label no_rows
## <fctr> <int>
## 1 1 5468
## 2 2 1
## 3 3 1
## 4 4 1
#plot using principal component anlaysis to reduce high-dimensional data to two dimensions
autoplot(
prcomp(model_ms[, 3:12], center = TRUE, scale. = TRUE),
data = model_ms,
colour = 'ms_label',
frame = TRUE
)
It appears that using h of 20 resulted in a reasonable model. It clustered the data points into 1 primary cluster with 22 anomalies.
#H = 20.0
#MeanShift clustering using multi-core processing
options(mc.cores = 2)
ms_clustering <-
msClustering(model_df_trans, h = 20.0, multi.core = TRUE)
#attach clustering labels to model df
model_ms <- model_df
model_ms[, 'Cluster'] <- ms_clustering[2]
#change labels to factors
model_ms[, 'Cluster'] <- as.factor(model_ms[, 'Cluster'])
#view factor levels of ms_label column
levels(model_ms$Cluster)
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14"
## [15] "15" "16" "17" "18" "19" "20" "21" "22" "23"
#view number of occurances per factor level
model_ms %>%
group_by(Cluster) %>%
summarise(no_rows = length(Cluster)) #cluster 1 has 5449 data points, clusters 2-23 have one point each.
## # A tibble: 23 x 2
## Cluster no_rows
## <fctr> <int>
## 1 1 5449
## 2 2 1
## 3 3 1
## 4 4 1
## 5 5 1
## 6 6 1
## 7 7 1
## 8 8 1
## 9 9 1
## 10 10 1
## # ... with 13 more rows
#principal component anlaysis to reduce high-dimensional data to two dimensions
fraud_PCA <- prcomp(model_ms[, 3:12], center = TRUE, scale. = TRUE)
fraud_PCA2 <- fraud_PCA$x[, 1:2]
#plot cluster 1 add anomalies as crosses.
plot(
fraud_PCA2,
main = "Credit Card Transaction Clusters",
sub = "Anomalies plotted as circles with red crosses",
cex.sub = 0.75,
font.sub = 3,
col.sub = "red"
)
points(fraud_PCA2[model_ms$Cluster != 1, ], pch = 4, col = "red")
#create DF that include possible fraud transactions
fraud <- model_df[model_ms$Cluster != 1,]
fraud <- fraud[, 1:2]
#view fraud
kable(fraud) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | |
|---|---|---|
| 35 | ARDMORE HIGHER EDUCATION CENTER | HOUSEHOLD APPLIANCE STORES |
| 279 | COMM. ON CONSUMER CREDIT | GOVERNMENT SERVICES–NOT ELSEWHERE CLASSIFIED |
| 293 | COMM. ON CONSUMER CREDIT | SHERATON |
| 327 | COMPSOURCE OKLAHOMA | DELTA |
| 1328 | DEPARTMENT OF REHABILITATION SERVICES | MISCELLANEOUS FOOD STORES-CONV STRS AND SPECIALTY MKTS. |
| 2159 | GRAND RIVER DAM AUTH. | COMMERCIAL EQUIPMENT, NOT ELSEWHERE CLASSIFIED |
| 2165 | GRAND RIVER DAM AUTH. | COMPUTERS, COMPUTER PERIPHERAL EQUIPMENT, SOFTWARE |
| 2174 | GRAND RIVER DAM AUTH. | DETECTIVE AGENCIES,PROTECTIVE AGENCIES,AND SECURITY SERVICES |
| 2194 | GRAND RIVER DAM AUTH. | GOVERNMENT SERVICES–NOT ELSEWHERE CLASSIFIED |
| 2614 | MENTAL HEALTH AND SUBSTANCE ABUSE SERV. | DEPARTMENT STORES |
| 2687 | MENTAL HEALTH AND SUBSTANCE ABUSE SERV. | RENAISSANCE HOTELS |
| 2713 | N. E. OKLA. A & M COLLEGE | AUTOMATED FUEL DISPENSER |
| 2752 | N. E. OKLA. A & M COLLEGE | RECORD STORES |
| 2782 | OFFICE OF JUVENILE AFFAIRS | COMFORT HOTEL INTERNATIONAL |
| 2975 | OFFICE OF MANAGEMENT AND ENTERPRISE SERV | TOLLS AND BRIDGE FEES |
| 3330 | OKLA. CITY COMMUNITY COLLEGE | GROCERY STORES,AND SUPERMARKETS |
| 3485 | OKLA. PANHANDLE STATE UNIV. | RECORD STORES |
| 4165 | REDLANDS COMMUNITY COLLEGE | LUXOR HOTEL AND CASINO |
| 4713 | STATE DEPARTMENT OF HEALTH | MISCELLANEOUS GENERAL MERCHANDISE |
| 4717 | STATE DEPARTMENT OF HEALTH | NON-DURABLE GOODS NOT ELSEWHERE CLASSIFIED |
| 4752 | STATE ELECTION BOARD | STATIONERY,OFFICE AND SCHOOL SUPPLY STORES |
| 5156 | UNIV.OF SCIENCE & ARTS OF OK | COMFORT HOTEL INTERNATIONAL |
Agency transactions that occurred within the merchant category listed in the fraud data frame could possibly be fraud based on my MeanShift analysis. Transactions that occurred within these merchant categories at these agencies require further analysis to determine if fraud actually occurred. Grand River Dam Auth had the highest number of merchant categories, 4, that might contain fraudulent transactions.
#Plot number of merchant categories that contain
#possible fraudulent transaactions by agency
ggplot(data = fraud, mapping = aes(Agency_Name)) + geom_bar(fill = 'blue', stat = "count") + xlab("Agency Name") + ylab("Number of Merchant Categories \nContaining Possible Fraudulent Transactions") + ggtitle("Possible Fraudulent Transactions") + coord_flip()
Autoencoder is an unsupervised, neural network algorithm that uses backpropagation, setting the target values equal to the inputs. Autoencoders compress the input into a latent-space representation, and then reconstructs the output from this representation. It is typically used for dimension reduction.
Hyperparameters tuned: Hidden layers: 5, 2, 5 and 10, 2, 10 Epochs: 50, 100, 200
#load libraries
library(h2o)
library(dplyr)
library(ggplot2)
h2o.init()
##
## H2O is not running yet, starting it now...
##
## Note: In case of errors look at the following log files:
## /var/folders/k6/qqdfd67942d5xb06yvglzqcr0000gn/T//RtmpxlEoPQ/h2o_meganroesch_started_from_r.out
## /var/folders/k6/qqdfd67942d5xb06yvglzqcr0000gn/T//RtmpxlEoPQ/h2o_meganroesch_started_from_r.err
##
##
## Starting H2O JVM and connecting: .. Connection successful!
##
## R is connected to the H2O cluster:
## H2O cluster uptime: 3 seconds 757 milliseconds
## H2O cluster timezone: America/New_York
## H2O data parsing timezone: UTC
## H2O cluster version: 3.20.0.2
## H2O cluster version age: 2 months and 7 days
## H2O cluster name: H2O_started_from_R_meganroesch_gjo928
## H2O cluster total nodes: 1
## H2O cluster total memory: 3.56 GB
## H2O cluster total cores: 4
## H2O cluster allowed cores: 4
## H2O cluster healthy: TRUE
## H2O Connection ip: localhost
## H2O Connection port: 54321
## H2O Connection proxy: NA
## H2O Internal Security: FALSE
## H2O API Extensions: XGBoost, Algos, AutoML, Core V3, Core V4
## R Version: R version 3.4.1 (2017-06-30)
# convert data to H2OFrame
model_h <- as.h2o(model_df_scale)
##
|
| | 0%
|
|=================================================================| 100%
#view head of h20 model
kable(head(model_h))
| Max_201307 | Max_201308 | Max_201309 | Max_201310 | Max_201311 | Max_201312 | Max_201401 | Max_201402 | Max_201403 | Max_201404 | Max_201405 | Max_201406 | Med_201307 | Med_201308 | Med_201309 | Med_201310 | Med_201311 | Med_201312 | Med_201401 | Med_201402 | Med_201403 | Med_201404 | Med_201405 | Med_201406 | MaxR_201307 | MaxR_201308 | MaxR_201309 | MaxR_201310 | MaxR_201311 | MaxR_201312 | MaxR_201401 | MaxR_201402 | MaxR_201403 | MaxR_201404 | MaxR_201405 | MaxR_201406 | MedR_201307 | MedR_201308 | MedR_201309 | MedR_201310 | MedR_201311 | MedR_201312 | MedR_201401 | MedR_201402 | MedR_201403 | MedR_201404 | MedR_201405 | MedR_201406 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0680335 | -0.0248850 | -0.3637536 | -0.2787139 | 0.0135197 | -0.3160999 | 0.7760440 | -0.382932 | -0.282552 | -0.2563837 | -0.3200084 | -0.3912933 | 0.0764192 | -0.1097998 | -0.1824873 | -0.1424242 | -0.1040116 | -0.0607806 | 0.4894809 | -0.2397345 | -0.225765 | -0.0861667 | -0.1588062 | -0.1746778 | -0.0822195 | -0.0218471 | -0.4295344 | -0.454398 | -0.4239034 | -0.356182 | 1.5626181 | -0.420211 | -0.4670037 | -0.4740046 | -0.4624106 | -0.4950477 | 0.7991785 | 1.0560317 | -0.2099764 | -0.2398453 | -0.1999642 | -0.1119167 | 1.4874624 | -0.1204337 | -0.1413479 | -0.1252074 | -0.1417702 | -0.0967447 |
| 0.0877499 | 0.0126459 | -0.3637536 | -0.2787139 | 0.0135197 | 0.3290033 | 0.2536490 | -0.382932 | -0.282552 | -0.2563837 | -0.3200084 | -0.3912933 | 0.1117813 | 0.1166292 | -0.1824873 | -0.1424242 | -0.1040116 | -0.0501229 | 0.0759417 | -0.2397345 | -0.225765 | -0.0861667 | -0.1588062 | -0.1746778 | 2.7737374 | -0.3783296 | 2.6082066 | 3.823477 | 5.0523924 | -0.356182 | -0.3954704 | -0.420211 | -0.4670037 | -0.4740046 | -0.4624106 | -0.4950477 | 5.0890480 | -0.2174755 | -0.2099764 | 1.2078064 | -0.1999642 | -0.1119167 | -0.0789986 | -0.1204337 | -0.1413479 | -0.1252074 | -0.1417702 | -0.0967447 |
| 0.1829367 | -0.0125401 | -0.1284096 | 2.2689856 | 0.0135197 | 0.0492077 | -0.1967417 | -0.382932 | -0.282552 | -0.2563837 | -0.3200084 | -0.3912933 | 0.0423153 | 0.0545474 | -0.0397959 | 0.2235111 | -0.1040116 | -0.0079566 | -0.1019518 | -0.2397345 | -0.225765 | -0.0861667 | -0.1588062 | -0.1746778 | 1.7840282 | 0.1865581 | -0.4295344 | 3.950616 | 0.6432722 | -0.356182 | -0.3954704 | -0.420211 | -0.4670037 | -0.4740046 | -0.4624106 | -0.4950477 | 18.6590433 | 3.7303969 | -0.2099764 | 2.6554580 | -0.1999642 | -0.1119167 | -0.0789986 | -0.1204337 | -0.1413479 | -0.1252074 | -0.1417702 | -0.0967447 |
| -0.0479014 | 0.0074599 | -0.3637536 | -0.2787139 | 0.0135197 | 0.7641744 | 0.6836222 | -0.382932 | -0.282552 | -0.2563837 | -0.3200084 | -0.3912933 | -0.1339843 | -0.0893996 | -0.1824873 | -0.1424242 | 0.1135489 | 0.0403034 | -0.0026706 | -0.2397345 | -0.225765 | -0.0861667 | -0.1588062 | -0.1746778 | -0.3053578 | 1.5023331 | 0.8022325 | -0.454398 | -0.4239034 | 1.931456 | 0.1618381 | -0.420211 | -0.4670037 | -0.4740046 | -0.4624106 | -0.4950477 | -0.3389502 | 1.5371345 | 0.2073472 | -0.2398453 | -0.1999642 | 0.8449992 | 0.0769432 | -0.1204337 | -0.1413479 | -0.1252074 | -0.1417702 | -0.0967447 |
| 0.0364684 | -0.0269110 | -0.3637536 | 0.3158198 | 0.0135197 | -0.3160999 | -0.1967417 | -0.382932 | -0.282552 | -0.2563837 | -0.3200084 | -0.3912933 | 0.0950119 | -0.1291786 | -0.1824873 | 0.0698889 | -0.1040116 | -0.0607806 | -0.1019518 | -0.2397345 | -0.225765 | -0.0861667 | -0.1588062 | -0.1746778 | -0.3053578 | -0.3783296 | -0.4295344 | 1.019262 | -0.4239034 | -0.356182 | -0.3954704 | -0.420211 | -0.4670037 | -0.4740046 | -0.4624106 | -0.4950477 | -0.3389502 | -0.2174755 | -0.2099764 | 0.4839806 | -0.1999642 | -0.1119167 | -0.0789986 | -0.1204337 | -0.1413479 | -0.1252074 | -0.1417702 | -0.0967447 |
| -0.0147671 | -0.0269110 | 1.1309317 | 1.5839023 | 0.0135197 | 0.1503852 | -0.1570854 | -0.382932 | -0.282552 | -0.2563837 | -0.3200084 | -0.3912933 | -0.0322229 | -0.1291786 | 0.1423728 | 0.1418943 | -0.1040116 | 0.0007853 | -0.0801584 | -0.2397345 | -0.225765 | -0.0861667 | -0.1588062 | -0.1746778 | -0.3053578 | 1.4148604 | 0.8288322 | 1.736543 | -0.4239034 | 4.317895 | -0.3954704 | -0.420211 | -0.4670037 | -0.4740046 | -0.4624106 | -0.4950477 | -0.3389502 | 0.2760086 | 0.5412060 | 0.4839806 | -0.1999642 | 0.4007168 | -0.0789986 | -0.1204337 | -0.1413479 | -0.1252074 | -0.1417702 | -0.0967447 |
#splitting the dataset into training and test sets
model_train_test <- h2o.splitFrame(model_h,
ratios = c(0.4, 0.4), # must add up to less than 1.0
seed = 42)
train <- model_train_test[[1]]
test1 <- model_train_test[[2]]
test2 <- model_train_test[[3]]
dim(train)
## [1] 2184 48
dim(test1)
## [1] 2206 48
dim(test2)
## [1] 1081 48
#set features
x_col <- colnames(model_df_scale)
#Hyperparameters: hidden= 5,2,5 epochs = 100
#unsupervised neural network model using deep learning autoencoders (autoencoder = TRUE)
#“bottleneck” training, hidden layer in the middle is very small. Model will reduce the dimensionality of the input data (in this case, down to 2 nodes/dimensions).
model <- h2o.deeplearning(
x = x_col,
training_frame = train,
model_id = "model",
autoencoder = TRUE,
hidden = c(5, 2, 5),
epochs = 100,
activation = "Tanh"
)
##
|
| | 0%
|
|====== | 10%
|
|======================================= | 60%
|
|=================================================================| 100%
#view model details
model
## Model Details:
## ==============
##
## H2OAutoEncoderModel: deeplearning
## Model ID: model
## Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 560 weights/biases, 16.5 KB, 218,400 training samples, mini-batch size 1
## layer units type dropout l1 l2 mean_rate rate_rms momentum
## 1 1 48 Input 0.00 %
## 2 2 5 Tanh 0.00 % 0.000000 0.000000 0.521347 0.338643 0.000000
## 3 3 2 Tanh 0.00 % 0.000000 0.000000 0.038802 0.013525 0.000000
## 4 4 5 Tanh 0.00 % 0.000000 0.000000 0.019534 0.006614 0.000000
## 5 5 48 Tanh 0.000000 0.000000 0.024856 0.041152 0.000000
## mean_weight weight_rms mean_bias bias_rms
## 1
## 2 -0.083713 0.230006 0.226451 0.970561
## 3 -0.009294 0.579821 0.236353 0.115837
## 4 -0.240070 0.800421 0.009668 0.806640
## 5 0.006262 0.122727 -0.040154 0.056141
##
##
## H2OAutoEncoderMetrics: deeplearning
## ** Reported on training data. **
##
## Training Set Metrics:
## =====================
##
## MSE: (Extract with `h2o.mse`) 0.002650377
## RMSE: (Extract with `h2o.rmse`) 0.05148181
#Test1
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test1_col <-
h2o.deepfeatures(model, test1, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|================================ | 50%
|
|=================================================================| 100%
ggplot(test1_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers based on the graph
#use anomaly detection function
#anomaly detection
anomaly <- h2o.anomaly(model, test1) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse
## mean
## 1 1.647652e+25
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly df
anomaly <- anomaly %>%
mutate(outlier = ifelse(Reconstruction.MSE > 1.647652e+25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier <-
anomaly[which(anomaly[, 2] > 1.647652e+25), ] #row 1659 looks to be an anomaly
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier, colour =
"red") +
geom_text(data = outlier,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions row 1659 of test1 is equal to row 4165 of the model_df
fraud_auto <- model_df[4165, ]
#Test2
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test2_col <-
h2o.deepfeatures(model, test2, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test2_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point()
#anomaly detection
anomaly2 <- h2o.anomaly(model, test2) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly2 %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #0.007633034
## mean
## 1 0.007556506
#plot
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly2 df
anomaly2 <- anomaly2 %>%
mutate(outlier = ifelse(Reconstruction.MSE > 0.25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier2 <-
anomaly2[which(anomaly2[, 2] > 0.25), ] #4 possible anomalies
#plot, possibly anomaly points are colored red
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier2, colour =
"red") + geom_text(data = outlier2,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions
#row 532 of test2 is equal to row 2687 of the model_df
#row 537 of test2 is equal to row 2713 of the model_df
#row 589 of test2 is equal to row 573 of the model_df
#row 937 of test2 is equal to row 4752 of the model_df
fraud_auto2 <- model_df[c(2687, 2713, 573, 4752), ]
fraud_auto <- rbind(fraud_auto, fraud_auto2)
#Hyperparameters: hidden= 10,2,10 epochs = 100
model <- h2o.deeplearning(
x = x_col,
training_frame = train,
model_id = "model",
autoencoder = TRUE,
hidden = c(10, 2, 10),
epochs = 100,
activation = "Tanh"
)
##
|
| | 0%
|
|============= | 20%
|
|========================== | 40%
|
|======================================= | 60%
|
|========================================================== | 90%
|
|=================================================================| 100%
#view model details
model
## Model Details:
## ==============
##
## H2OAutoEncoderModel: deeplearning
## Model ID: model
## Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 1,070 weights/biases, 22.6 KB, 218,400 training samples, mini-batch size 1
## layer units type dropout l1 l2 mean_rate rate_rms momentum
## 1 1 48 Input 0.00 %
## 2 2 10 Tanh 0.00 % 0.000000 0.000000 0.277385 0.307664 0.000000
## 3 3 2 Tanh 0.00 % 0.000000 0.000000 0.012270 0.003171 0.000000
## 4 4 10 Tanh 0.00 % 0.000000 0.000000 0.011503 0.006643 0.000000
## 5 5 48 Tanh 0.000000 0.000000 0.015042 0.024994 0.000000
## mean_weight weight_rms mean_bias bias_rms
## 1
## 2 -0.015015 0.205557 0.178328 0.735836
## 3 0.185515 0.466652 -0.096877 0.300828
## 4 0.104532 0.606931 -0.105371 0.745774
## 5 0.005170 0.156369 -0.083767 0.171909
##
##
## H2OAutoEncoderMetrics: deeplearning
## ** Reported on training data. **
##
## Training Set Metrics:
## =====================
##
## MSE: (Extract with `h2o.mse`) 0.002555075
## RMSE: (Extract with `h2o.rmse`) 0.05054775
#Test1
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test1_col <-
h2o.deepfeatures(model, test1, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|================================ | 50%
|
|=================================================================| 100%
ggplot(test1_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see which points are outliers, use anomaly detection
#anomaly detection
anomaly <- h2o.anomaly(model, test1) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #1.647652e+25
## mean
## 1 1.647652e+25
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly df
anomaly <- anomaly %>%
mutate(outlier = ifelse(Reconstruction.MSE > 1.647652e+25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier <-
anomaly[which(anomaly[, 2] > 1.647652e+25), ] #again row 1659 looks to be an anomaly
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier, colour =
"red") +
geom_text(data = outlier,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions row 1659 of test1 is equal to row 4165 of the model_df
fraud_auto3 <- model_df[4165, ]
#Test2
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test2_col <-
h2o.deepfeatures(model, test2, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test2_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly detection function
#anomaly detection
anomaly2 <- h2o.anomaly(model, test2) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly2 %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #0.007471474
## mean
## 1 0.007480511
#plot
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly2 df
anomaly2 <- anomaly2 %>%
mutate(outlier = ifelse(Reconstruction.MSE > 0.25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier2 <-
anomaly2[which(anomaly2[, 2] > 0.25), ] #again, 4 possible anomalies
#plot, possibly anomaly points are colored red
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier2, colour =
"red") + geom_text(data = outlier2,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions
#row 532 of test2 is equal to row 2687 of the model_df
#row 537 of test2 is equal to row 2713 of the model_df
#row 589 of test2 is equal to row 573 of the model_df
#row 937 of test2 is equal to row 4752 of the model_df
fraud_auto4 <- model_df[c(2687, 2713, 573, 4752), ]
fraud_auto3 <- rbind(fraud_auto3, fraud_auto4)
#Hyperparameters: hidden= 5,2,5 epochs = 50
model <- h2o.deeplearning(
x = x_col,
training_frame = train,
model_id = "model",
autoencoder = TRUE,
hidden = c(5, 2, 5),
epochs = 50,
activation = "Tanh"
)
##
|
| | 0%
|
|====== | 10%
|
|=================================================================| 100%
#view model details
model
## Model Details:
## ==============
##
## H2OAutoEncoderModel: deeplearning
## Model ID: model
## Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 560 weights/biases, 16.5 KB, 109,200 training samples, mini-batch size 1
## layer units type dropout l1 l2 mean_rate rate_rms momentum
## 1 1 48 Input 0.00 %
## 2 2 5 Tanh 0.00 % 0.000000 0.000000 0.431818 0.305530 0.000000
## 3 3 2 Tanh 0.00 % 0.000000 0.000000 0.036133 0.016090 0.000000
## 4 4 5 Tanh 0.00 % 0.000000 0.000000 0.016816 0.005639 0.000000
## 5 5 48 Tanh 0.000000 0.000000 0.021853 0.031536 0.000000
## mean_weight weight_rms mean_bias bias_rms
## 1
## 2 -0.042468 0.195081 0.182341 0.497439
## 3 -0.282667 0.364345 -0.060672 0.202292
## 4 0.053229 0.638863 0.354854 0.205578
## 5 0.030075 0.145544 -0.014504 0.041839
##
##
## H2OAutoEncoderMetrics: deeplearning
## ** Reported on training data. **
##
## Training Set Metrics:
## =====================
##
## MSE: (Extract with `h2o.mse`) 0.002688596
## RMSE: (Extract with `h2o.rmse`) 0.05185167
#Test1
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test1_col <-
h2o.deepfeatures(model, test1, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|================================ | 50%
|
|=================================================================| 100%
ggplot(test1_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly detection function
#anomaly detection
anomaly <- h2o.anomaly(model, test1) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #1.647652e+25
## mean
## 1 1.647652e+25
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly df
anomaly <- anomaly %>%
mutate(outlier = ifelse(Reconstruction.MSE > 1.647652e+25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier <-
anomaly[which(anomaly[, 2] > 1.647652e+25), ] #row 1659 looks to be an anomaly
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier, colour =
"red") +
geom_text(data = outlier,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions row 1659 of test1 is equal to row 4165 of the model_df
fraud_auto5 <- model_df[4165, ]
#Test2
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test2_col <-
h2o.deepfeatures(model, test2, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test2_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly function
#anomaly detection
anomaly2 <- h2o.anomaly(model, test2) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly2 %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #0.007654928
## mean
## 1 0.007638525
#plot
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly2 df
anomaly2 <- anomaly2 %>%
mutate(outlier = ifelse(Reconstruction.MSE > 0.25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier2 <-
anomaly2[which(anomaly2[, 2] > 0.25), ] #4 possible anomalies
#plot, possibly anomaly points are colored red
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier2, colour =
"red") + geom_text(data = outlier2,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions
#row 532 of test2 is equal to row 2687 of the model_df
#row 537 of test2 is equal to row 2713 of the model_df
#row 589 of test2 is equal to row 573 of the model_df
#row 937 of test2 is equal to row 4752 of the model_df
fraud_auto6 <- model_df[c(2687, 2713, 573, 4752), ]
fraud_auto5 <- rbind(fraud_auto5, fraud_auto5)
#Hyperparameters: hidden= 10,2,10 epochs = 50
model <- h2o.deeplearning(
x = x_col,
training_frame = train,
model_id = "model",
autoencoder = TRUE,
hidden = c(10, 2, 10),
epochs = 50,
activation = "Tanh"
)
##
|
| | 0%
|
|====== | 10%
|
|==================================================== | 80%
|
|=================================================================| 100%
#view model details
model
## Model Details:
## ==============
##
## H2OAutoEncoderModel: deeplearning
## Model ID: model
## Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 1,070 weights/biases, 22.6 KB, 109,200 training samples, mini-batch size 1
## layer units type dropout l1 l2 mean_rate rate_rms momentum
## 1 1 48 Input 0.00 %
## 2 2 10 Tanh 0.00 % 0.000000 0.000000 0.461852 0.310685 0.000000
## 3 3 2 Tanh 0.00 % 0.000000 0.000000 0.041602 0.013158 0.000000
## 4 4 10 Tanh 0.00 % 0.000000 0.000000 0.011628 0.002403 0.000000
## 5 5 48 Tanh 0.000000 0.000000 0.035009 0.056452 0.000000
## mean_weight weight_rms mean_bias bias_rms
## 1
## 2 0.004638 0.199317 0.067262 0.493608
## 3 0.048928 0.334327 -0.018171 0.056111
## 4 -0.006798 0.460786 0.118686 0.297196
## 5 0.010035 0.160927 -0.015447 0.059579
##
##
## H2OAutoEncoderMetrics: deeplearning
## ** Reported on training data. **
##
## Training Set Metrics:
## =====================
##
## MSE: (Extract with `h2o.mse`) 0.002695308
## RMSE: (Extract with `h2o.rmse`) 0.05191636
#Test1
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test1_col <-
h2o.deepfeatures(model, test1, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test1_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly function
#anomaly detection
anomaly <- h2o.anomaly(model, test1) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #1.647652e+25
## mean
## 1 1.647652e+25
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly df
anomaly <- anomaly %>%
mutate(outlier = ifelse(Reconstruction.MSE > 1.647652e+25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier <-
anomaly[which(anomaly[, 2] > 1.647652e+25), ] #row 1659 looks to be an anomaly
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier, colour =
"red") +
geom_text(data = outlier,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions row 1659 of test1 is equal to row 4165 of the model_df
fraud_auto7 <- model_df[4165, ]
#Test2
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test2_col <-
h2o.deepfeatures(model, test2, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test2_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly function
#anomaly detection
anomaly2 <- h2o.anomaly(model, test2) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly2 %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #0.007580477
## mean
## 1 0.007654478
#plot
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly2 df
anomaly2 <- anomaly2 %>%
mutate(outlier = ifelse(Reconstruction.MSE > 0.25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier2 <-
anomaly2[which(anomaly2[, 2] > 0.25), ] #4 possible anomalies
#plot, possibly anomaly points are colored red
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier2, colour =
"red") + geom_text(data = outlier2,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions
#row 532 of test2 is equal to row 2687 of the model_df
#row 537 of test2 is equal to row 2713 of the model_df
#row 589 of test2 is equal to row 573 of the model_df
#row 937 of test2 is equal to row 4752 of the model_df
fraud_auto8 <- model_df[c(2687, 2713, 573, 4752), ]
fraud_auto7 <- rbind(fraud_auto7, fraud_auto8)
#Hyperparameters: hidden= 5,2,5 epochs = 200
model <- h2o.deeplearning(
x = x_col,
training_frame = train,
model_id = "model",
autoencoder = TRUE,
hidden = c(5, 2, 5),
epochs = 200,
activation = "Tanh"
)
##
|
| | 0%
|
|=== | 5%
|
|==================== | 30%
|
|======================================= | 60%
|
|========================================================== | 90%
|
|=================================================================| 100%
#view model details
model
## Model Details:
## ==============
##
## H2OAutoEncoderModel: deeplearning
## Model ID: model
## Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 560 weights/biases, 16.5 KB, 436,800 training samples, mini-batch size 1
## layer units type dropout l1 l2 mean_rate rate_rms momentum
## 1 1 48 Input 0.00 %
## 2 2 5 Tanh 0.00 % 0.000000 0.000000 0.647445 0.339183 0.000000
## 3 3 2 Tanh 0.00 % 0.000000 0.000000 0.031419 0.020157 0.000000
## 4 4 5 Tanh 0.00 % 0.000000 0.000000 0.021343 0.007451 0.000000
## 5 5 48 Tanh 0.000000 0.000000 0.015609 0.027358 0.000000
## mean_weight weight_rms mean_bias bias_rms
## 1
## 2 0.089554 0.236167 -0.698669 0.968084
## 3 -0.004764 0.729381 0.232981 0.304356
## 4 0.587888 0.754158 -0.968423 0.921102
## 5 -0.031601 0.132699 -0.105433 0.133616
##
##
## H2OAutoEncoderMetrics: deeplearning
## ** Reported on training data. **
##
## Training Set Metrics:
## =====================
##
## MSE: (Extract with `h2o.mse`) 0.002673703
## RMSE: (Extract with `h2o.rmse`) 0.05170786
#Test1
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test1_col <-
h2o.deepfeatures(model, test1, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|================================ | 50%
|
|=================================================================| 100%
ggplot(test1_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #hard to see outliers, use anomaly detection
#anomaly detection
anomaly <- h2o.anomaly(model, test1) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #1.647652e+25
## mean
## 1 1.647652e+25
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly df
anomaly <- anomaly %>%
mutate(outlier = ifelse(Reconstruction.MSE > 1.647652e+25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier <-
anomaly[which(anomaly[, 2] > 1.647652e+25), ] #row 1659 looks to be an anomaly
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier, colour =
"red") +
geom_text(data = outlier,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions row 1659 of test1 is equal to row 4165 of the model_df
fraud_auto9 <- model_df[4165, ]
#Test2
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test2_col <-
h2o.deepfeatures(model, test2, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test2_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly detection function
#anomaly detection
anomaly2 <- h2o.anomaly(model, test2) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly2 %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #0.007565647
## mean
## 1 0.007585463
#plot
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly2 df
anomaly2 <- anomaly2 %>%
mutate(outlier = ifelse(Reconstruction.MSE > 0.25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier2 <-
anomaly2[which(anomaly2[, 2] > 0.25), ] #4 possible anomalies
#plot, possibly anomaly points are colored red
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier2, colour =
"red") + geom_text(data = outlier2,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions
#row 532 of test2 is equal to row 2687 of the model_df
#row 537 of test2 is equal to row 2713 of the model_df
#row 589 of test2 is equal to row 573 of the model_df
#row 937 of test2 is equal to row 4752 of the model_df
fraud_auto10 <- model_df[c(2687, 2713, 573, 4752), ]
fraud_auto9 <- rbind(fraud_auto9, fraud_auto10)
#Hyperparameters: hidden= 10,2,10 epochs = 200
#unsupervised neural network model using deep learning autoencoders (autoencoder = TRUE)
#“bottleneck” training, hidden layer in the middle is very small. Model will reduce the dimensionality of the input data (in this case, down to 2 nodes/dimensions).
model <- h2o.deeplearning(
x = x_col,
training_frame = train,
model_id = "model",
autoencoder = TRUE,
hidden = c(10, 2, 10),
epochs = 200,
activation = "Tanh"
)
##
|
| | 0%
|
|=== | 5%
|
|============= | 20%
|
|========================== | 40%
|
|======================================= | 60%
|
|==================================================== | 80%
|
|============================================================== | 95%
|
|=================================================================| 100%
#view model details
model
## Model Details:
## ==============
##
## H2OAutoEncoderModel: deeplearning
## Model ID: model
## Status of Neuron Layers: auto-encoder, gaussian distribution, Quadratic loss, 1,070 weights/biases, 22.6 KB, 436,800 training samples, mini-batch size 1
## layer units type dropout l1 l2 mean_rate rate_rms momentum
## 1 1 48 Input 0.00 %
## 2 2 10 Tanh 0.00 % 0.000000 0.000000 0.453684 0.340695 0.000000
## 3 3 2 Tanh 0.00 % 0.000000 0.000000 0.020535 0.012176 0.000000
## 4 4 10 Tanh 0.00 % 0.000000 0.000000 0.028887 0.023118 0.000000
## 5 5 48 Tanh 0.000000 0.000000 0.015156 0.031581 0.000000
## mean_weight weight_rms mean_bias bias_rms
## 1
## 2 -0.039354 0.246624 0.206902 0.887383
## 3 0.177691 0.465519 -0.046751 0.053148
## 4 0.154542 0.838174 -0.084232 1.084916
## 5 -0.003295 0.138534 -0.116243 0.147573
##
##
## H2OAutoEncoderMetrics: deeplearning
## ** Reported on training data. **
##
## Training Set Metrics:
## =====================
##
## MSE: (Extract with `h2o.mse`) 0.002489549
## RMSE: (Extract with `h2o.rmse`) 0.04989538
#Test1
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test1_col <-
h2o.deepfeatures(model, test1, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|================================ | 50%
|
|=================================================================| 100%
ggplot(test1_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly detection function
#anomaly detection
anomaly <- h2o.anomaly(model, test1) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #1.647652e+25
## mean
## 1 1.647652e+25
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly df
anomaly <- anomaly %>%
mutate(outlier = ifelse(Reconstruction.MSE > 1.647652e+25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier <-
anomaly[which(anomaly[, 2] > 1.647652e+25), ] #row 1659 looks to be an anomaly
#plot
ggplot(anomaly, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier, colour =
"red") +
geom_text(data = outlier,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions row 1659 of test1 is equal to row 4165 of the model_df
fraud_auto11 <- model_df[4165, ]
#Test2
#dimensionality reduction to explore feature space
#extract this hidden feature and plot it to show the reduced #representation of the input data.
test2_col <-
h2o.deepfeatures(model, test2, layer = 2) %>% as.data.frame()
##
|
| | 0%
|
|=================================================================| 100%
ggplot(test2_col, aes(x = DF.L2.C1, y = DF.L2.C2)) +
geom_point() #difficult to see outliers, use anomaly detection function
#anomaly detection
anomaly2 <- h2o.anomaly(model, test2) %>%
as.data.frame() %>%
tibble::rownames_to_column()
mean_mse <- anomaly2 %>%
summarise(mean = mean(Reconstruction.MSE))
mean_mse #0.007465285
## mean
## 1 0.007415878
#plot
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1")
#add outlier vs no outlier to anomaly2 df
anomaly2 <- anomaly2 %>%
mutate(outlier = ifelse(Reconstruction.MSE > 0.25, "outlier", "no_outlier"))
#subset which rows greater than mean mse
outlier2 <-
anomaly2[which(anomaly2[, 2] > 0.25), ] #4 possible anomalies
#plot, possibly anomaly points are colored red
ggplot(anomaly2, aes(x = as.numeric(rowname), y = Reconstruction.MSE)) +
geom_point(alpha = 0.3) +
geom_hline(data = mean_mse, aes(yintercept = mean)) +
scale_color_brewer(palette = "Set1") +
labs(x = "Row Number", y = "Reconstruction MSE") + geom_point(data = outlier2, colour =
"red") + geom_text(data = outlier2,
label = "Anomaly",
vjust = 1)
#create DF that include possible fraud transactions
#row 532 of test2 is equal to row 2687 of the model_df
#row 537 of test2 is equal to row 2713 of the model_df
#row 589 of test2 is equal to row 573 of the model_df
#row 937 of test2 is equal to row 4752 of the model_df
fraud_auto12 <- model_df[c(2687, 2713, 573, 4752), ]
fraud_auto11 <- rbind(fraud_auto11, fraud_auto12)
#all versions of tuned hyperparameters resulted in the same outliers
#view fraud_auto dataframe
kable(fraud_auto) %>% kable_styling(latex_options = "scale_down")
| Agency_Name | Merchant_Category | Max_201307 | Max_201308 | Max_201309 | Max_201310 | Max_201311 | Max_201312 | Max_201401 | Max_201402 | Max_201403 | Max_201404 | Max_201405 | Max_201406 | Mean_201307 | Mean_201308 | Mean_201309 | Mean_201310 | Mean_201311 | Mean_201312 | Mean_201401 | Mean_201402 | Mean_201403 | Mean_201404 | Mean_201405 | Mean_201406 | Med_201307 | Med_201308 | Med_201309 | Med_201310 | Med_201311 | Med_201312 | Med_201401 | Med_201402 | Med_201403 | Med_201404 | Med_201405 | Med_201406 | MaxR_201307 | MaxR_201308 | MaxR_201309 | MaxR_201310 | MaxR_201311 | MaxR_201312 | MaxR_201401 | MaxR_201402 | MaxR_201403 | MaxR_201404 | MaxR_201405 | MaxR_201406 | MeanR_201307 | MeanR_201308 | MeanR_201309 | MeanR_201310 | MeanR_201311 | MeanR_201312 | MeanR_201401 | MeanR_201402 | MeanR_201403 | MeanR_201404 | MeanR_201405 | MeanR_201406 | MedR_201307 | MedR_201308 | MedR_201309 | MedR_201310 | MedR_201311 | MedR_201312 | MedR_201401 | MedR_201402 | MedR_201403 | MedR_201404 | MedR_201405 | MedR_201406 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4165 | REDLANDS COMMUNITY COLLEGE | LUXOR HOTEL AND CASINO | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -2.421811e+16 | 0.0000000 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.000000 | 0.000000 | 0.0000000 | 0.000000 | 1.0000000 | 0.0000000 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.00000 | 0.000000 | 0.0000000 | 0.0000000 | 1.0000000 | 0.0000000 | 0 | 0 | 0 | 0 | 0.00 | 0.0000000 | 0 | 0.000000 | 0.000000 | 0.00 | 2 | 0.000000 | 0.000000 | 0.000000 | 0 | 0 | 0.000000 | 0.000000 | 0 | 0.0000 | 0.000 | 0.0 | 1 | 0.000 | 0.0 | 0.000 | 0 | 0 | 0.0 | 0.0 | 0 | 0.0 | 0 | 0 | 1 | 0.00 | 0 | 0 | 0 | 0 | 0.000000 | 0.0000000 |
| 2687 | MENTAL HEALTH AND SUBSTANCE ABUSE SERV. | RENAISSANCE HOTELS | 1.773986 | 1.656732 | 0.000000 | 0.000000 | 7.434916e-01 | 2.9160310 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 1.773986 | 1.656732 | 0.0000000 | 0.000000 | 0.7434916 | 2.9160314 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 1.42751 | 1.333156 | 0.0000000 | 0.0000000 | 0.5982806 | 2.3465029 | 0 | 0 | 0 | 0 | 0.00 | 0.0000000 | 0 | 2.264151 | 1.509434 | 0.00 | 0 | 1.283019 | 0.000000 | 4.603774 | 0 | 0 | 0.000000 | 0.000000 | 0 | 0.0625 | 0.375 | 0.0 | 0 | 0.125 | 0.0 | 0.375 | 0 | 0 | 0.0 | 0.0 | 0 | 60.0 | 6 | 0 | 0 | 17.00 | 0 | 0 | 0 | 0 | 0.000000 | 0.0000000 |
| 2713 | N. E. OKLA. A & M COLLEGE | AUTOMATED FUEL DISPENSER | 0.000000 | 0.000000 | 1.234737 | 1.349614 | 0.000000e+00 | 0.4567655 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.000000 | 0.000000 | 1.1525040 | 1.119113 | 0.0000000 | 0.4567655 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.00000 | 0.000000 | 1.0768340 | 1.0456345 | 0.0000000 | 0.4267753 | 0 | 0 | 0 | 0 | 0.00 | 0.0000000 | 0 | 0.000000 | 0.000000 | 0.05 | 0 | 3.950000 | 0.000000 | 0.000000 | 0 | 0 | 0.000000 | 0.000000 | 0 | 0.0000 | 0.250 | 0.5 | 0 | 0.250 | 0.0 | 0.000 | 0 | 0 | 0.0 | 0.0 | 0 | 0.0 | 0 | 1 | 0 | 158.00 | 0 | 0 | 0 | 0 | 0.000000 | 0.0000000 |
| 573 | DEPARTMENT OF AGRICULTURE | HOLIDAY INNS | 0.000000 | 0.000000 | 1.657086 | 2.485629 | 1.181337e+00 | 3.7576390 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.000000 | 0.000000 | 0.8285429 | 1.059845 | 1.1813372 | 1.5486041 | 0 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.00000 | 0.000000 | 0.6666667 | 0.8916667 | 1.4258009 | 1.5158658 | 0 | 0 | 0 | 0 | 0.00 | 0.0000000 | 0 | 1.479290 | 3.846154 | 0.00 | 0 | 3.846154 | 3.106509 | 0.000000 | 0 | 0 | 0.000000 | 0.000000 | 0 | 0.3200 | 0.120 | 0.0 | 0 | 0.160 | 0.2 | 0.000 | 0 | 0 | 0.0 | 0.0 | 0 | 0.5 | 0 | 0 | 0 | 3.25 | 1 | 0 | 0 | 0 | 0.000000 | 0.0000000 |
| 4752 | STATE ELECTION BOARD | STATIONERY,OFFICE AND SCHOOL SUPPLY STORES | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000e+00 | 4.9158030 | 0 | 0 | 0 | 0 | 0.0748956 | 0.0050097 | 0.000000 | 0.000000 | 0.0000000 | 0.000000 | 0.0000000 | 4.9158030 | 0 | 0 | 0 | 0 | 0.0379237 | 0.0041748 | 0.00000 | 0.000000 | 0.0000000 | 0.0000000 | 0.0000000 | 981.2500000 | 0 | 0 | 0 | 0 | 7.57 | 0.8333333 | 0 | 0.000000 | 0.000000 | 0.00 | 0 | 0.000000 | 0.000000 | 0.000000 | 0 | 0 | 3.180723 | 0.313253 | 0 | 0.0000 | 0.000 | 0.0 | 0 | 0.000 | 0.0 | 0.000 | 0 | 0 | 0.5 | 0.5 | 0 | 0.0 | 0 | 0 | 0 | 0.00 | 0 | 0 | 0 | 0 | 4.606061 | 0.4242424 |
Agency transactions that occurred within the merchant category listed in the fraud_auto data frame could possibly be fraud based on my Autoencoder analysis. Transactions that occurred within these merchant categories at these agencies require further analysis to determine if fraud actually occurred.
Of the five agency transactions flagged as possible anomalies using Autoencoder, all but one was also flagged with my MeanShift model. The one data point that was flagged by Autoencoder but not MeanShift was the Holiday Inns category of the Department of Agriculture.
Overall, I found using Autoencoder more challenging for anomaly detection than MeanShift as the model did not cluster data points.
#Plot number of merchant categories that contain
#possible fraudulent transaactions by agency
ggplot(data = fraud_auto, mapping = aes(Agency_Name)) + geom_bar(fill = 'blue', stat = "count") + xlab("Agency Name") + ylab("Number of Merchant Categories \nContaining Possible Fraudulent Transactions") + ggtitle("Possible Fraudulent Transactions") + coord_flip()